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<a href=#2 id=2 data-nosnippet>2</a>//!
<a href=#3 id=3 data-nosnippet>3</a>//! This module provides a comprehensive set of parallel processing utilities designed
<a href=#4 id=4 data-nosnippet>4</a>//! for high-performance computing scenarios. It offers both immediate sequential
<a href=#5 id=5 data-nosnippet>5</a>//! implementations and extensible interfaces for future parallel execution backends.
<a href=#6 id=6 data-nosnippet>6</a>//!
<a href=#7 id=7 data-nosnippet>7</a>//! ## Architecture Overview
<a href=#8 id=8 data-nosnippet>8</a>//!
<a href=#9 id=9 data-nosnippet>9</a>//! The module follows a **parallel-ready design pattern** where functions provide:
<a href=#10 id=10 data-nosnippet>10</a>//! - **Immediate usability**: All functions work correctly with sequential processing
<a href=#11 id=11 data-nosnippet>11</a>//! - **Future extensibility**: Interfaces designed to easily integrate parallel backends
<a href=#12 id=12 data-nosnippet>12</a>//! - **Consistent API**: Unified function signatures across all operations
<a href=#13 id=13 data-nosnippet>13</a>//! - **Performance monitoring**: Built-in timing and statistics collection
<a href=#14 id=14 data-nosnippet>14</a>//!
<a href=#15 id=15 data-nosnippet>15</a>//! ## Current Implementation
<a href=#16 id=16 data-nosnippet>16</a>//!
<a href=#17 id=17 data-nosnippet>17</a>//! Currently, all functions use **sequential processing** with the following characteristics:
<a href=#18 id=18 data-nosnippet>18</a>//! - **Thread-safe**: All operations are safe to call from any thread context
<a href=#19 id=19 data-nosnippet>19</a>//! - **Memory efficient**: Minimal overhead beyond standard library operations
<a href=#20 id=20 data-nosnippet>20</a>//! - **Composable**: Functions can be chained and combined naturally
<a href=#21 id=21 data-nosnippet>21</a>//! - **Observable**: Performance monitoring and logging built-in
<a href=#22 id=22 data-nosnippet>22</a>//!
<a href=#23 id=23 data-nosnippet>23</a>//! ## Function Categories
<a href=#24 id=24 data-nosnippet>24</a>//!
<a href=#25 id=25 data-nosnippet>25</a>//! ### Core Operations
<a href=#26 id=26 data-nosnippet>26</a>//! - [`parallel_map`] - Transform each element with a function
<a href=#27 id=27 data-nosnippet>27</a>//! - [`parallel_filter`] - Filter elements based on predicates
<a href=#28 id=28 data-nosnippet>28</a>//! - [`parallel_for_each`] - Execute side effects on each element
<a href=#29 id=29 data-nosnippet>29</a>//! - [`parallel_fold`] - Reduce elements to a single value
<a href=#30 id=30 data-nosnippet>30</a>//!
<a href=#31 id=31 data-nosnippet>31</a>//! ### Data Organization
<a href=#32 id=32 data-nosnippet>32</a>//! - [`parallel_partition`] - Split data into matching/non-matching groups
<a href=#33 id=33 data-nosnippet>33</a>//! - [`parallel_group_by`] - Group elements by computed keys
<a href=#34 id=34 data-nosnippet>34</a>//! - [`parallel_chunks`] - Divide data into fixed-size chunks
<a href=#35 id=35 data-nosnippet>35</a>//! - [`parallel_windows`] - Create sliding windows over data
<a href=#36 id=36 data-nosnippet>36</a>//!
<a href=#37 id=37 data-nosnippet>37</a>//! ### Data Cleaning
<a href=#38 id=38 data-nosnippet>38</a>//! - [`parallel_dedup`] - Remove consecutive duplicates
<a href=#39 id=39 data-nosnippet>39</a>//! - [`parallel_sort`] - Sort data (currently sequential)
<a href=#40 id=40 data-nosnippet>40</a>//! - [`parallel_search`] - Search for elements (currently sequential)
<a href=#41 id=41 data-nosnippet>41</a>//!
<a href=#42 id=42 data-nosnippet>42</a>//! ### Advanced Features
<a href=#43 id=43 data-nosnippet>43</a>//! - [`parallel_map_async`] - Asynchronous parallel mapping with concurrency control
<a href=#44 id=44 data-nosnippet>44</a>//! - [`parallel_map_with_cancellation`] - Cancellable parallel operations
<a href=#45 id=45 data-nosnippet>45</a>//! - [`monitored_execute`] - Performance-monitored function execution
<a href=#46 id=46 data-nosnippet>46</a>//! - [`create_work_queue`] - Work-stealing task queues
<a href=#47 id=47 data-nosnippet>47</a>//! - [`distribute_work`] - Load-balanced work distribution
<a href=#48 id=48 data-nosnippet>48</a>//!
<a href=#49 id=49 data-nosnippet>49</a>//! ### Monitoring & Observability
<a href=#50 id=50 data-nosnippet>50</a>//! - [`ThreadPoolMonitor`] - Performance statistics and monitoring
<a href=#51 id=51 data-nosnippet>51</a>//! - [`ThreadPoolStats`] - Detailed execution metrics
<a href=#52 id=52 data-nosnippet>52</a>//! - [`OperationTimer`] - Automatic operation timing
<a href=#53 id=53 data-nosnippet>53</a>//!
<a href=#54 id=54 data-nosnippet>54</a>//! ## Usage Patterns
<a href=#55 id=55 data-nosnippet>55</a>//!
<a href=#56 id=56 data-nosnippet>56</a>//! ### Basic Parallel Processing
<a href=#57 id=57 data-nosnippet>57</a>//! ```rust
<a href=#58 id=58 data-nosnippet>58</a>//! use trash_analyzer::parallel::*;
<a href=#59 id=59 data-nosnippet>59</a>//!
<a href=#60 id=60 data-nosnippet>60</a>//! // Transform data
<a href=#61 id=61 data-nosnippet>61</a>//! let data = vec![1, 2, 3, 4, 5];
<a href=#62 id=62 data-nosnippet>62</a>//! let doubled = parallel_map(data, |x| x * 2);
<a href=#63 id=63 data-nosnippet>63</a>//!
<a href=#64 id=64 data-nosnippet>64</a>//! // Filter and process
<a href=#65 id=65 data-nosnippet>65</a>//! let filtered = parallel_filter(doubled, |&x| x > 5);
<a href=#66 id=66 data-nosnippet>66</a>//!
<a href=#67 id=67 data-nosnippet>67</a>//! // Group by criteria
<a href=#68 id=68 data-nosnippet>68</a>//! let groups = parallel_group_by(filtered, |&x| x % 3);
<a href=#69 id=69 data-nosnippet>69</a>//! ```
<a href=#70 id=70 data-nosnippet>70</a>//!
<a href=#71 id=71 data-nosnippet>71</a>//! ### Performance Monitoring
<a href=#72 id=72 data-nosnippet>72</a>//! ```rust
<a href=#73 id=73 data-nosnippet>73</a>//! use trash_analyzer::parallel::{ThreadPoolMonitor, monitored_execute};
<a href=#74 id=74 data-nosnippet>74</a>//!
<a href=#75 id=75 data-nosnippet>75</a>//! let monitor = ThreadPoolMonitor::new();
<a href=#76 id=76 data-nosnippet>76</a>//!
<a href=#77 id=77 data-nosnippet>77</a>//! let result = monitored_execute(&monitor, "expensive_operation", || {
<a href=#78 id=78 data-nosnippet>78</a>//! // Your expensive computation here
<a href=#79 id=79 data-nosnippet>79</a>//! 42
<a href=#80 id=80 data-nosnippet>80</a>//! });
<a href=#81 id=81 data-nosnippet>81</a>//!
<a href=#82 id=82 data-nosnippet>82</a>//! println!("Stats: {:?}", monitor.stats());
<a href=#83 id=83 data-nosnippet>83</a>//! ```
<a href=#84 id=84 data-nosnippet>84</a>//!
<a href=#85 id=85 data-nosnippet>85</a>//! ### Asynchronous Processing
<a href=#86 id=86 data-nosnippet>86</a>//! ```rust,no_run
<a href=#87 id=87 data-nosnippet>87</a>//! use trash_analyzer::parallel::parallel_map_async;
<a href=#88 id=88 data-nosnippet>88</a>//!
<a href=#89 id=89 data-nosnippet>89</a>//! async fn process_async() {
<a href=#90 id=90 data-nosnippet>90</a>//! let data = vec![1, 2, 3, 4, 5];
<a href=#91 id=91 data-nosnippet>91</a>//!
<a href=#92 id=92 data-nosnippet>92</a>//! // Process up to 3 items concurrently
<a href=#93 id=93 data-nosnippet>93</a>//! let results = parallel_map_async(data, |x| async move {
<a href=#94 id=94 data-nosnippet>94</a>//! // Simulate async work
<a href=#95 id=95 data-nosnippet>95</a>//! x * 2
<a href=#96 id=96 data-nosnippet>96</a>//! }, 3).await;
<a href=#97 id=97 data-nosnippet>97</a>//! }
<a href=#98 id=98 data-nosnippet>98</a>//! ```
<a href=#99 id=99 data-nosnippet>99</a>//!
<a href=#100 id=100 data-nosnippet>100</a>//! ### Work Distribution
<a href=#101 id=101 data-nosnippet>101</a>//! ```rust
<a href=#102 id=102 data-nosnippet>102</a>//! use trash_analyzer::parallel::distribute_work;
<a href=#103 id=103 data-nosnippet>103</a>//!
<a href=#104 id=104 data-nosnippet>104</a>//! let data = vec![1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
<a href=#105 id=105 data-nosnippet>105</a>//!
<a href=#106 id=106 data-nosnippet>106</a>//! // Distribute work across chunks
<a href=#107 id=107 data-nosnippet>107</a>//! let results = distribute_work(&data, |chunk| {
<a href=#108 id=108 data-nosnippet>108</a>//! chunk.iter().sum::<i32>()
<a href=#109 id=109 data-nosnippet>109</a>//! });
<a href=#110 id=110 data-nosnippet>110</a>//! ```
<a href=#111 id=111 data-nosnippet>111</a>//!
<a href=#112 id=112 data-nosnippet>112</a>//! ## Performance Considerations
<a href=#113 id=113 data-nosnippet>113</a>//!
<a href=#114 id=114 data-nosnippet>114</a>//! ### When to Use Sequential vs Parallel
<a href=#115 id=115 data-nosnippet>115</a>//! - **Small datasets**: Sequential processing often faster due to overhead
<a href=#116 id=116 data-nosnippet>116</a>//! - **Large datasets**: Parallel processing scales better with data size
<a href=#117 id=117 data-nosnippet>117</a>//! - **I/O bound operations**: Async variants provide better concurrency
<a href=#118 id=118 data-nosnippet>118</a>//! - **CPU bound operations**: Future parallel backends will excel here
<a href=#119 id=119 data-nosnippet>119</a>//!
<a href=#120 id=120 data-nosnippet>120</a>//! ### Memory Usage
<a href=#121 id=121 data-nosnippet>121</a>//! - **Streaming**: Most operations process data in a single pass
<a href=#122 id=122 data-nosnippet>122</a>//! - **Allocation**: Results collected into new containers
<a href=#123 id=123 data-nosnippet>123</a>//! - **Cloning**: Some operations require `Clone` for windowing operations
<a href=#124 id=124 data-nosnippet>124</a>//!
<a href=#125 id=125 data-nosnippet>125</a>//! ### Thread Safety
<a href=#126 id=126 data-nosnippet>126</a>//! - **Send + Sync**: All data types must be thread-safe for future parallelization
<a href=#127 id=127 data-nosnippet>127</a>//! - **Interior mutability**: Use appropriate synchronization primitives
<a href=#128 id=128 data-nosnippet>128</a>//! - **Shared state**: Avoid unless explicitly designed for concurrency
<a href=#129 id=129 data-nosnippet>129</a>//!
<a href=#130 id=130 data-nosnippet>130</a>//! ## Future Extensions
<a href=#131 id=131 data-nosnippet>131</a>//!
<a href=#132 id=132 data-nosnippet>132</a>//! The module is designed for easy integration of parallel execution backends:
<a href=#133 id=133 data-nosnippet>133</a>//!
<a href=#134 id=134 data-nosnippet>134</a>//! ### Planned Parallel Backends
<a href=#135 id=135 data-nosnippet>135</a>//! - **Rayon integration**: Drop-in parallel iterators
<a href=#136 id=136 data-nosnippet>136</a>//! - **Fork-join pools**: Work-stealing thread pools
<a href=#137 id=137 data-nosnippet>137</a>//! - **GPU acceleration**: CUDA/OpenCL for compute-intensive operations
<a href=#138 id=138 data-nosnippet>138</a>//! - **Distributed processing**: Multi-node parallel execution
<a href=#139 id=139 data-nosnippet>139</a>//!
<a href=#140 id=140 data-nosnippet>140</a>//! ### Extension Points
<a href=#141 id=141 data-nosnippet>141</a>//! - **Backend traits**: Pluggable execution strategies
<a href=#142 id=142 data-nosnippet>142</a>//! - **Configuration**: Runtime backend selection
<a href=#143 id=143 data-nosnippet>143</a>//! - **Fallbacks**: Automatic fallback to sequential on errors
<a href=#144 id=144 data-nosnippet>144</a>//! - **Metrics**: Detailed performance profiling
<a href=#145 id=145 data-nosnippet>145</a>//!
<a href=#146 id=146 data-nosnippet>146</a>//! ## Error Handling
<a href=#147 id=147 data-nosnippet>147</a>//!
<a href=#148 id=148 data-nosnippet>148</a>//! Functions follow Rust's error handling patterns:
<a href=#149 id=149 data-nosnippet>149</a>//! - **Result types**: Operations that can fail return `Result<T, E>`
<a href=#150 id=150 data-nosnippet>150</a>//! - **Option types**: Operations that may not produce results return `Option<T>`
<a href=#151 id=151 data-nosnippet>151</a>//! - **Cancellation**: Graceful handling of cancellation tokens
<a href=#152 id=152 data-nosnippet>152</a>//! - **Logging**: Comprehensive error logging
<a href=#153 id=153 data-nosnippet>153</a>//!
<a href=#154 id=154 data-nosnippet>154</a>//! ## Dependencies
<a href=#155 id=155 data-nosnippet>155</a>//!
<a href=#156 id=156 data-nosnippet>156</a>//! The module relies on several key crates:
<a href=#157 id=157 data-nosnippet>157</a>//! - `fork_union`: Thread pool and parallel execution (imported but not yet used)
<a href=#158 id=158 data-nosnippet>158</a>//! - `parking_lot`: Efficient synchronization primitives
<a href=#159 id=159 data-nosnippet>159</a>//! - `smol`: Async runtime for channel-based operations
<a href=#160 id=160 data-nosnippet>160</a>//! - `smol_cancellation_token`: Cancellation support for async operations
<a href=#161 id=161 data-nosnippet>161</a>//!
<a href=#162 id=162 data-nosnippet>162</a>//! ## Testing
<a href=#163 id=163 data-nosnippet>163</a>//!
<a href=#164 id=164 data-nosnippet>164</a>//! The module includes comprehensive tests covering:
<a href=#165 id=165 data-nosnippet>165</a>//! - **Functional correctness**: All operations produce expected results
<a href=#166 id=166 data-nosnippet>166</a>//! - **Edge cases**: Empty inputs, single elements, large datasets
<a href=#167 id=167 data-nosnippet>167</a>//! - **Performance**: Benchmarks comparing sequential vs future parallel
<a href=#168 id=168 data-nosnippet>168</a>//! - **Concurrency**: Thread safety and race condition testing
<a href=#169 id=169 data-nosnippet>169</a>//! - **Error handling**: Proper error propagation and recovery
<a href=#170 id=170 data-nosnippet>170</a>//!
<a href=#171 id=171 data-nosnippet>171</a>//! ## Examples
<a href=#172 id=172 data-nosnippet>172</a>//!
<a href=#173 id=173 data-nosnippet>173</a>//! See the individual function documentation for detailed examples.
<a href=#174 id=174 data-nosnippet>174</a>//! For more complex usage patterns, check the integration tests.
<a href=#175 id=175 data-nosnippet>175</a>
<a href=#176 id=176 data-nosnippet>176</a></span><span class="kw">pub mod </span>advanced;
<a href=#177 id=177 data-nosnippet>177</a><span class="kw">pub mod </span>core;
<a href=#178 id=178 data-nosnippet>178</a><span class="kw">pub mod </span>data;
<a href=#179 id=179 data-nosnippet>179</a><span class="kw">pub mod </span>organize;
<a href=#180 id=180 data-nosnippet>180</a>
<a href=#181 id=181 data-nosnippet>181</a><span class="kw">pub use </span>advanced::<span class="kw-2">*</span>;
<a href=#182 id=182 data-nosnippet>182</a><span class="kw">pub use </span>core::<span class="kw-2">*</span>;
<a href=#183 id=183 data-nosnippet>183</a><span class="kw">pub use </span>data::<span class="kw-2">*</span>;
<a href=#184 id=184 data-nosnippet>184</a><span class="kw">pub use </span>organize::<span class="kw-2">*</span>;</code></pre></div></section></main></body></html>