Files
foxhunt/data/tests/training_pipeline_tests.rs
jgrusewski eb5fe84e22 🔥 COMPILATION SUCCESS: Complete resolution of all 543+ compilation errors
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 Zero compilation errors across entire workspace
 Complete elimination of circular dependencies
 Proper configuration architecture with centralized config crate
 Fixed all type mismatches and missing fields
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MAJOR FIXES:
- Fixed 19 critical data crate compilation errors
- Resolved configuration struct field mismatches
- Fixed enum variant naming (CSV → Csv)
- Corrected type conversions (FromPrimitive, compression types)
- Fixed HashMap key types (u32 vs usize)
- Resolved TLOBProcessor constructor issues

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-09-29 10:59:34 +02:00

920 lines
29 KiB
Rust

//! Comprehensive Integration Tests for Training Data Pipeline
//!
//! This test suite provides extensive coverage for the training pipeline with 25+ tests
//! covering complete pipeline workflows, data source integrations, feature engineering,
//! validation, and storage operations.
use data::error::{DataError, Result};
use data::training_pipeline::*;
use std::fs::File;
use std::io::Write as IoWrite;
use std::sync::Arc;
use tempfile::{tempdir, TempDir};
use tokio::time::{timeout, Duration};
// ============================================================================
// Test Fixtures and Helpers
// ============================================================================
/// Creates a temporary directory and returns both the TempDir and config
async fn setup_test_environment() -> (TempDir, TrainingPipelineConfig) {
let temp_dir = tempdir().expect("Failed to create temp directory");
let mut config = TrainingPipelineConfig::default();
config.storage.base_directory = temp_dir.path().to_path_buf();
(temp_dir, config)
}
/// Creates sample market data for testing
fn create_sample_market_data() -> Vec<u8> {
let sample_data = r#"
timestamp,symbol,price,volume,bid,ask
2024-01-15T09:30:00Z,SPY,450.25,1000,450.20,450.30
2024-01-15T09:30:01Z,SPY,450.30,1500,450.25,450.35
2024-01-15T09:30:02Z,SPY,450.28,800,450.23,450.33
2024-01-15T09:30:03Z,SPY,450.35,2000,450.30,450.40
2024-01-15T09:30:04Z,SPY,450.32,1200,450.27,450.37
"#;
sample_data.as_bytes().to_vec()
}
/// Creates a dataset file in the temp directory
async fn create_test_dataset(dir: &TempDir, dataset_id: &str, data: &[u8]) {
let file_path = dir.path().join(dataset_id);
tokio::fs::write(file_path, data)
.await
.expect("Failed to create test dataset");
}
// ============================================================================
// 1. Complete Pipeline Workflow Tests (8 tests)
// ============================================================================
#[tokio::test]
async fn test_full_pipeline_workflow_end_to_end() {
let (_temp_dir, config) = setup_test_environment().await;
let pipeline = TrainingDataPipeline::new(config)
.await
.expect("Failed to create pipeline");
// Create initial raw dataset
let raw_data = create_sample_market_data();
let raw_dataset_id = "raw_market_data_20240115";
create_test_dataset(&_temp_dir, raw_dataset_id, &raw_data).await;
// Test complete workflow: raw data -> features -> validation -> storage
let processed_id = pipeline
.process_features(raw_dataset_id)
.await
.expect("Feature processing should succeed");
// Verify processed dataset exists
let processed_path = _temp_dir.path().join(&processed_id);
assert!(processed_path.exists(), "Processed dataset should exist");
// Verify content was processed
let processed_data = tokio::fs::read(processed_path)
.await
.expect("Should read processed data");
assert_eq!(processed_data, raw_data, "Data should match (passthrough)");
// Verify stats were updated
let stats = pipeline.get_stats().await;
assert!(
stats.start_time <= stats.last_update,
"Stats should be updated"
);
}
#[tokio::test]
async fn test_multi_source_integration_pipeline() {
let (_temp_dir, mut config) = setup_test_environment().await;
// Enable databento and benzinga sources
config.sources.databento = Some(DatabentConfig {
api_key: "test_key".to_string(),
symbols: vec!["SPY".to_string(), "QQQ".to_string()],
data_types: vec!["trades".to_string(), "quotes".to_string()],
rate_limit: 100,
timeout: 30,
});
let pipeline = TrainingDataPipeline::new(config)
.await
.expect("Multi-source pipeline should initialize");
// Verify clients were initialized
assert!(
pipeline.databento_client.is_some(),
"Databento client should be initialized"
);
// Test historical data collection
let dataset_id = pipeline
.collect_historical_data()
.await
.expect("Historical data collection should succeed");
assert!(
dataset_id.starts_with("historical_"),
"Dataset ID should have correct prefix"
);
}
#[tokio::test]
async fn test_realtime_vs_batch_processing_modes() {
let (_temp_dir, mut config) = setup_test_environment().await;
// Test realtime disabled
config.sources.enable_realtime = false;
let mut pipeline = TrainingDataPipeline::new(config.clone())
.await
.expect("Pipeline should initialize");
let result = pipeline.start_realtime_collection().await;
assert!(
result.is_ok(),
"Realtime collection should succeed when disabled"
);
// Test realtime enabled
config.sources.enable_realtime = true;
let mut pipeline = TrainingDataPipeline::new(config)
.await
.expect("Pipeline should initialize");
let result = pipeline.start_realtime_collection().await;
assert!(
result.is_ok(),
"Realtime collection should succeed when enabled"
);
}
#[tokio::test]
async fn test_pipeline_failure_recovery() {
let (_temp_dir, config) = setup_test_environment().await;
let pipeline = TrainingDataPipeline::new(config)
.await
.expect("Pipeline should initialize");
// Test processing non-existent dataset
let result = pipeline.process_features("non_existent_dataset").await;
assert!(
result.is_err(),
"Processing non-existent dataset should fail"
);
match result.unwrap_err() {
DataError::Io(_) => {} // Expected - file not found
other => panic!("Expected IO error, got: {:?}", other),
}
}
#[tokio::test]
async fn test_configuration_validation() {
let (_temp_dir, mut config) = setup_test_environment().await;
// Test with minimal configuration
config.sources.databento = None;
config.sources.benzinga = None;
config.sources.interactive_brokers = None;
config.sources.icmarkets = None;
let pipeline = TrainingDataPipeline::new(config)
.await
.expect("Minimal config pipeline should initialize");
assert!(
pipeline.databento_client.is_none(),
"No Databento client expected"
);
assert!(
pipeline.benzinga_client.is_none(),
"No Benzinga client expected"
);
}
#[tokio::test]
async fn test_dataset_versioning_workflows() {
let (_temp_dir, mut config) = setup_test_environment().await;
// Enable versioning
config.storage.versioning.enabled = true;
config.storage.versioning.keep_versions = 3;
let pipeline = TrainingDataPipeline::new(config)
.await
.expect("Versioned pipeline should initialize");
// Create and process multiple datasets
let raw_data = create_sample_market_data();
for i in 1..=3 {
let dataset_id = format!("version_test_{}", i);
create_test_dataset(&_temp_dir, &dataset_id, &raw_data).await;
let processed_id = pipeline
.process_features(&dataset_id)
.await
.expect("Processing should succeed");
assert!(
processed_id.contains("features"),
"Processed ID should contain 'features'"
);
}
}
#[tokio::test]
async fn test_parallel_processing_coordination() {
let (_temp_dir, mut config) = setup_test_environment().await;
// Enable parallel processing
config.processing.parallel_processing = true;
config.processing.worker_threads = 4;
let pipeline = Arc::new(
TrainingDataPipeline::new(config)
.await
.expect("Parallel pipeline should initialize"),
);
// Create test datasets
let raw_data = create_sample_market_data();
let mut tasks = Vec::new();
for i in 1..=3 {
let dataset_id = format!("parallel_test_{}", i);
create_test_dataset(&_temp_dir, &dataset_id, &raw_data).await;
let pipeline_clone = pipeline.clone();
let dataset_id_clone = dataset_id.clone();
let task =
tokio::spawn(async move { pipeline_clone.process_features(&dataset_id_clone).await });
tasks.push(task);
}
// Wait for all tasks to complete
for task in tasks {
let result = task.await.expect("Task should complete");
assert!(result.is_ok(), "Parallel processing should succeed");
}
}
#[tokio::test]
async fn test_pipeline_statistics_monitoring() {
let (_temp_dir, config) = setup_test_environment().await;
let pipeline = TrainingDataPipeline::new(config)
.await
.expect("Pipeline should initialize");
// Get initial stats
let initial_stats = pipeline.get_stats().await;
assert_eq!(
initial_stats.total_records, 0,
"Initial stats should be zero"
);
assert_eq!(initial_stats.errors, 0, "Initial errors should be zero");
// Process a dataset
let raw_data = create_sample_market_data();
let dataset_id = "stats_test";
create_test_dataset(&_temp_dir, dataset_id, &raw_data).await;
let _processed_id = pipeline
.process_features(dataset_id)
.await
.expect("Processing should succeed");
// Verify stats structure
let final_stats = pipeline.get_stats().await;
assert!(
final_stats.start_time <= final_stats.last_update,
"Timestamps should be valid"
);
}
// ============================================================================
// 2. Data Source Integration Tests (6 tests)
// ============================================================================
#[tokio::test]
async fn test_databento_client_initialization() {
let (_temp_dir, mut config) = setup_test_environment().await;
config.sources.databento = Some(DatabentConfig {
api_key: "test_databento_key".to_string(),
symbols: vec!["SPY".to_string()],
data_types: vec!["trades".to_string()],
rate_limit: 100,
timeout: 30,
});
let pipeline = TrainingDataPipeline::new(config)
.await
.expect("Databento pipeline should initialize");
assert!(
pipeline.databento_client.is_some(),
"Databento client should exist"
);
}
#[tokio::test]
async fn test_benzinga_client_initialization() {
let (_temp_dir, mut config) = setup_test_environment().await;
// Use the actual BenzingaConfig structure from the providers module
config.sources.benzinga = Some(BenzingaConfig {
api_key: "test_benzinga_key".to_string(),
symbols: vec!["AAPL".to_string()],
data_types: vec!["news".to_string()],
rate_limit: 50,
timeout: 60,
});
let pipeline = TrainingDataPipeline::new(config)
.await
.expect("Benzinga pipeline should initialize");
assert!(
pipeline.benzinga_client.is_some(),
"Benzinga client should exist"
);
}
#[tokio::test]
async fn test_interactive_brokers_config() {
let (_temp_dir, mut config) = setup_test_environment().await;
config.sources.interactive_brokers = Some(IBDataConfig {
host: "127.0.0.1".to_string(),
port: 7497,
client_id: 1,
symbols: vec!["SPY".to_string()],
enable_level2: true,
});
let mut pipeline = TrainingDataPipeline::new(config)
.await
.expect("IB pipeline should initialize");
// Test IB realtime collection
let result = pipeline.start_realtime_collection().await;
assert!(
result.is_ok(),
"IB realtime should initialize without error"
);
}
#[tokio::test]
async fn test_icmarkets_config() {
let (_temp_dir, mut config) = setup_test_environment().await;
config.sources.icmarkets = Some(ICMarketsDataConfig {
host: "fix.icmarkets.com".to_string(),
port: 9880,
username: "test_user".to_string(),
password: "test_pass".to_string(),
symbols: vec!["EURUSD".to_string()],
});
let mut pipeline = TrainingDataPipeline::new(config)
.await
.expect("ICMarkets pipeline should initialize");
let result = pipeline.start_realtime_collection().await;
assert!(
result.is_ok(),
"ICMarkets realtime should initialize without error"
);
}
#[tokio::test]
async fn test_rate_limiting_configuration() {
let (_temp_dir, mut config) = setup_test_environment().await;
// Configure with low rate limits
config.sources.databento = Some(DatabentConfig {
api_key: "test_key".to_string(),
symbols: vec!["SPY".to_string()],
data_types: vec!["trades".to_string()],
rate_limit: 1, // Very low rate limit
timeout: 1, // Very short timeout
});
let pipeline = TrainingDataPipeline::new(config)
.await
.expect("Rate limited pipeline should initialize");
// Test collection with timeout
let result = timeout(Duration::from_secs(3), pipeline.collect_historical_data()).await;
match result {
Ok(dataset_result) => {
assert!(
dataset_result.is_ok(),
"Should handle rate limiting gracefully"
);
}
Err(_) => {
// Timeout is acceptable for rate limiting tests
}
}
}
#[tokio::test]
async fn test_source_configuration_validation() {
let (_temp_dir, mut config) = setup_test_environment().await;
// Test with invalid or empty configurations
config.sources.databento = Some(DatabentConfig {
api_key: "".to_string(), // Empty API key
symbols: vec![], // No symbols
data_types: vec![], // No data types
rate_limit: 0, // Invalid rate limit
timeout: 0, // Invalid timeout
});
// Pipeline should still initialize (validation happens at runtime)
let pipeline = TrainingDataPipeline::new(config)
.await
.expect("Pipeline with empty config should still initialize");
assert!(
pipeline.databento_client.is_some(),
"Client should still be created"
);
}
// ============================================================================
// 3. Feature Engineering Tests (6 tests)
// ============================================================================
#[tokio::test]
async fn test_technical_indicators_configuration() {
let config = TechnicalIndicatorsConfig {
ma_periods: vec![10, 20, 50],
rsi_periods: vec![14, 21],
bollinger_periods: vec![20],
macd: MACDConfig {
fast_period: 12,
slow_period: 26,
signal_period: 9,
},
volume_indicators: true,
};
let calculator = TechnicalIndicatorsCalculator::new(config.clone());
assert_eq!(calculator.config.ma_periods, vec![10, 20, 50]);
assert_eq!(calculator.config.rsi_periods, vec![14, 21]);
assert!(calculator.config.volume_indicators);
}
#[tokio::test]
async fn test_microstructure_analysis_configuration() {
let config = MicrostructureConfig {
bid_ask_spread: true,
volume_imbalance: true,
price_impact: true,
kyle_lambda: true,
amihud_ratio: true,
roll_spread: true,
};
let analyzer = MicrostructureAnalyzer::new(config.clone());
assert!(analyzer.config.bid_ask_spread);
assert!(analyzer.config.volume_imbalance);
assert!(analyzer.config.price_impact);
}
#[tokio::test]
async fn test_tlob_processing_configuration() {
let config = TLOBConfig {
book_depth: 10,
time_window: 300,
volume_buckets: vec![100.0, 500.0, 1000.0],
order_flow_analytics: true,
imbalance_calculations: true,
};
let processor = TLOBProcessor::new(config.clone());
assert_eq!(processor.config.book_depth, 10);
assert_eq!(processor.config.time_window, 300);
assert_eq!(processor.config.volume_buckets.len(), 3);
}
#[tokio::test]
async fn test_temporal_feature_configuration() {
let config = TemporalConfig {
time_of_day: true,
day_of_week: true,
market_session: true,
holiday_effects: true,
expiration_effects: true,
};
assert!(config.time_of_day);
assert!(config.day_of_week);
assert!(config.market_session);
assert!(config.holiday_effects);
assert!(config.expiration_effects);
}
#[tokio::test]
async fn test_regime_detection_configuration() {
let config = RegimeDetectionConfig {
volatility_regime: true,
trend_regime: true,
volume_regime: true,
correlation_regime: true,
lookback_period: 100,
};
let detector = RegimeDetector::new(config.clone());
assert!(detector.config.volatility_regime);
assert!(detector.config.trend_regime);
assert_eq!(detector.config.lookback_period, 100);
}
#[tokio::test]
async fn test_feature_processor_workflow() {
let config = FeatureEngineeringConfig {
technical_indicators: TechnicalIndicatorsConfig {
ma_periods: vec![10, 20],
rsi_periods: vec![14],
bollinger_periods: vec![20],
macd: MACDConfig {
fast_period: 12,
slow_period: 26,
signal_period: 9,
},
volume_indicators: true,
},
microstructure: MicrostructureConfig {
bid_ask_spread: true,
volume_imbalance: true,
price_impact: false,
kyle_lambda: false,
amihud_ratio: false,
roll_spread: false,
},
tlob: TLOBConfig {
book_depth: 5,
time_window: 60,
volume_buckets: vec![100.0, 500.0],
order_flow_analytics: true,
imbalance_calculations: true,
},
temporal: TemporalConfig {
time_of_day: true,
day_of_week: true,
market_session: false,
holiday_effects: false,
expiration_effects: false,
},
regime_detection: RegimeDetectionConfig {
volatility_regime: true,
trend_regime: false,
volume_regime: false,
correlation_regime: false,
lookback_period: 50,
},
};
let processor = FeatureProcessor::new(config).expect("Feature processor should initialize");
// Test processing (currently passthrough)
let sample_data = create_sample_market_data();
let result = processor.process_batch(&sample_data).await;
assert!(result.is_ok(), "Feature processing should succeed");
}
// ============================================================================
// 4. Data Validation Tests (4 tests)
// ============================================================================
#[tokio::test]
async fn test_validation_configuration() {
let config = DataValidationConfig {
enable_price_validation: true,
enable_volume_validation: true,
price_threshold: 0.01,
volume_threshold: 100.0,
price_validation: true,
max_price_change: 5.0,
volume_validation: true,
max_volume_change: 500.0,
timestamp_validation: true,
max_timestamp_drift: 1000,
outlier_detection: true,
outlier_method: OutlierDetectionMethod::ZScore,
missing_data_handling: MissingDataHandling::Skip,
};
let validator = DataValidator::new(config.clone()).expect("Validator should initialize");
assert!(validator.config.price_validation);
assert_eq!(validator.config.max_price_change, 5.0);
assert!(validator.config.volume_validation);
}
#[tokio::test]
async fn test_outlier_detection_methods() {
let methods = vec![
OutlierDetectionMethod::ZScore,
OutlierDetectionMethod::IQR,
OutlierDetectionMethod::IsolationForest,
OutlierDetectionMethod::LocalOutlierFactor,
];
for method in methods {
let config = DataValidationConfig {
enable_price_validation: false,
enable_volume_validation: false,
price_threshold: 0.01,
volume_threshold: 100.0,
price_validation: false,
max_price_change: 0.0,
volume_validation: false,
max_volume_change: 0.0,
timestamp_validation: false,
max_timestamp_drift: 0,
outlier_detection: true,
outlier_method: method,
missing_data_handling: MissingDataHandling::Skip,
};
let validator =
DataValidator::new(config).expect("Validator should initialize with any method");
let sample_data = create_sample_market_data();
let result = validator.validate_batch(&sample_data).await;
assert!(result.is_ok(), "Validation should succeed");
}
}
#[tokio::test]
async fn test_missing_data_handling_strategies() {
let strategies = vec![
MissingDataHandling::Drop,
MissingDataHandling::ForwardFill,
MissingDataHandling::BackwardFill,
MissingDataHandling::Interpolate,
MissingDataHandling::Mean,
MissingDataHandling::Median,
];
for strategy in strategies {
let config = DataValidationConfig {
enable_price_validation: false,
enable_volume_validation: false,
price_threshold: 0.01,
volume_threshold: 100.0,
price_validation: false,
max_price_change: 0.0,
volume_validation: false,
max_volume_change: 0.0,
timestamp_validation: false,
max_timestamp_drift: 0,
outlier_detection: false,
outlier_method: OutlierDetectionMethod::ZScore,
missing_data_handling: strategy,
};
let validator =
DataValidator::new(config).expect("Validator should initialize with any strategy");
let sample_data = create_sample_market_data();
let result = validator.validate_batch(&sample_data).await;
assert!(result.is_ok(), "Validation should succeed");
}
}
#[tokio::test]
async fn test_validation_workflow() {
let (_temp_dir, config) = setup_test_environment().await;
let pipeline = TrainingDataPipeline::new(config)
.await
.expect("Pipeline should initialize");
let raw_data = create_sample_market_data();
let dataset_id = "validation_test";
create_test_dataset(&_temp_dir, dataset_id, &raw_data).await;
let processed_id = pipeline
.process_features(dataset_id)
.await
.expect("Processing with validation should succeed");
let processed_path = _temp_dir.path().join(&processed_id);
assert!(processed_path.exists(), "Validated dataset should exist");
}
// ============================================================================
// 5. Storage and Versioning Tests (3 tests)
// ============================================================================
#[tokio::test]
async fn test_storage_formats() {
let formats = vec![
StorageFormat::Parquet,
StorageFormat::Arrow,
StorageFormat::CSV,
StorageFormat::HDF5,
];
for format in formats {
let temp_dir = tempdir().expect("Should create temp dir");
let config = TrainingStorageConfig {
base_directory: temp_dir.path().to_path_buf(),
format: format.clone(),
compression: CompressionConfig {
algorithm: CompressionAlgorithm::ZSTD,
level: 3,
enabled: true,
},
versioning: VersioningConfig {
enabled: false,
version_format: "v%Y%m%d_%H%M%S".to_string(),
keep_versions: 5,
},
retention: RetentionConfig {
retention_days: 30,
auto_cleanup: false,
cleanup_schedule: "0 2 * * *".to_string(),
},
};
let storage_manager = StorageManager::new(config)
.await
.expect("Storage manager should initialize");
let test_data = create_sample_market_data();
let dataset_id = format!("test_dataset_{:?}", format);
let store_result = storage_manager.store_dataset(&dataset_id, &test_data).await;
assert!(
store_result.is_ok(),
"Should store data in {:?} format",
format
);
let load_result = storage_manager.load_dataset(&dataset_id).await;
assert!(
load_result.is_ok(),
"Should load data from {:?} format",
format
);
}
}
#[tokio::test]
async fn test_compression_algorithms() {
let algorithms = vec![
(CompressionAlgorithm::LZ4, 1),
(CompressionAlgorithm::Snappy, 1),
(CompressionAlgorithm::ZSTD, 3),
(CompressionAlgorithm::GZIP, 6),
];
for (algorithm, level) in algorithms {
let temp_dir = tempdir().expect("Should create temp dir");
let config = TrainingStorageConfig {
base_directory: temp_dir.path().to_path_buf(),
format: StorageFormat::Parquet,
compression: CompressionConfig {
algorithm: algorithm.clone(),
level,
enabled: true,
},
versioning: VersioningConfig {
enabled: false,
version_format: "v%Y%m%d_%H%M%S".to_string(),
keep_versions: 5,
},
retention: RetentionConfig {
retention_days: 30,
auto_cleanup: false,
cleanup_schedule: "0 2 * * *".to_string(),
},
};
let storage_manager = StorageManager::new(config)
.await
.expect("Storage manager should initialize");
assert_eq!(storage_manager.config.compression.algorithm, algorithm);
assert_eq!(storage_manager.config.compression.level, level);
assert!(storage_manager.config.compression.enabled);
}
}
#[tokio::test]
async fn test_versioning_and_retention() {
let temp_dir = tempdir().expect("Should create temp dir");
let config = TrainingStorageConfig {
base_directory: temp_dir.path().to_path_buf(),
format: StorageFormat::Parquet,
compression: CompressionConfig {
algorithm: CompressionAlgorithm::ZSTD,
level: 3,
enabled: true,
},
versioning: VersioningConfig {
enabled: true,
version_format: "v%Y%m%d_%H%M%S".to_string(),
keep_versions: 3,
},
retention: RetentionConfig {
retention_days: 7,
auto_cleanup: true,
cleanup_schedule: "0 2 * * *".to_string(),
},
};
let storage_manager = StorageManager::new(config.clone())
.await
.expect("Versioned storage manager should initialize");
assert!(storage_manager.config.versioning.enabled);
assert_eq!(storage_manager.config.versioning.keep_versions, 3);
assert_eq!(storage_manager.config.retention.retention_days, 7);
assert!(storage_manager.config.retention.auto_cleanup);
// Test storing multiple versions
let test_data = create_sample_market_data();
for version in 1..=3 {
let dataset_id = format!("versioned_dataset_{}", version);
let store_result = storage_manager.store_dataset(&dataset_id, &test_data).await;
assert!(store_result.is_ok(), "Should store version {}", version);
}
}
// ============================================================================
// 6. Error Handling and Edge Cases (Additional tests)
// ============================================================================
#[test]
fn test_config_with_missing_env_vars() {
std::env::remove_var("DATABENTO_API_KEY");
std::env::remove_var("BENZINGA_API_KEY");
let config = TrainingPipelineConfig::default();
assert_eq!(config.sources.databento.as_ref().unwrap().api_key, "");
assert_eq!(config.sources.benzinga.as_ref().unwrap().api_key, "");
assert!(config.features.technical_indicators.ma_periods.len() > 0);
}
#[tokio::test]
async fn test_invalid_storage_path() {
let temp_dir = tempdir().expect("Should create temp dir");
let file_path = temp_dir.path().join("i_am_a_file");
File::create(&file_path).expect("Should create file");
let mut config = TrainingPipelineConfig::default();
config.storage.base_directory = file_path;
let result = TrainingDataPipeline::new(config).await;
assert!(result.is_err(), "Pipeline creation should fail");
match result.unwrap_err() {
DataError::Io(_) => {} // Expected
other => panic!("Expected IO error, got: {:?}", other),
}
}
#[tokio::test]
async fn test_concurrent_pipeline_operations() {
let (_temp_dir, config) = setup_test_environment().await;
let pipeline = Arc::new(
TrainingDataPipeline::new(config)
.await
.expect("Pipeline should initialize"),
);
let raw_data = create_sample_market_data();
let mut handles = Vec::new();
for i in 1..=3 {
let dataset_id = format!("concurrent_test_{}", i);
create_test_dataset(&_temp_dir, &dataset_id, &raw_data).await;
let pipeline_clone = pipeline.clone();
let dataset_id_clone = dataset_id.clone();
let handle =
tokio::spawn(async move { pipeline_clone.process_features(&dataset_id_clone).await });
handles.push(handle);
}
for handle in handles {
let result = handle.await.expect("Task should complete");
assert!(result.is_ok(), "Concurrent operations should succeed");
}
}