added batching mess

This commit is contained in:
Bojan Kucera 2025-06-08 23:30:46 -04:00
parent fe96cf6679
commit 22992cd393
4 changed files with 603 additions and 95 deletions

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DEVELOPMENT-ROADMAP.md Normal file
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@ -0,0 +1,377 @@
# 📋 Stock Bot Development Roadmap
*Last Updated: June 2025*
## 🎯 Overview
This document outlines the development plan for the Stock Bot platform, focusing on building a robust data pipeline from market data providers through processing layers to trading execution. The plan emphasizes establishing solid foundational layers before adding advanced features.
## 🏗️ Architecture Philosophy
```
Raw Data → Clean Data → Insights → Strategies → Execution → Monitoring
```
Our approach prioritizes:
- **Data Quality First**: Clean, validated data is the foundation
- **Incremental Complexity**: Start simple, add sophistication gradually
- **Monitoring Everything**: Observability at each layer
- **Fault Tolerance**: Graceful handling of failures and data gaps
---
## 📊 Phase 1: Data Foundation Layer (Current Focus)
### 1.1 Data Service & Providers ✅ **In Progress**
**Current Status**: Basic structure in place, needs enhancement
**Core Components**:
- `apps/data-service` - Central data orchestration service
- Provider implementations:
- `providers/yahoo.provider.ts` ✅ Basic implementation
- `providers/quotemedia.provider.ts` ✅ Basic implementation
- `providers/proxy.provider.ts` ✅ Proxy/fallback logic
**Immediate Tasks**:
1. **Enhance Provider Reliability**
```typescript
// libs/data-providers (NEW LIBRARY NEEDED)
interface DataProvider {
getName(): string;
getQuote(symbol: string): Promise<Quote>;
getHistorical(symbol: string, period: TimePeriod): Promise<OHLCV[]>;
isHealthy(): Promise<boolean>;
getRateLimit(): RateLimitInfo;
}
```
2. **Add Rate Limiting & Circuit Breakers**
- Implement in `libs/http` client
- Add provider-specific rate limits
- Circuit breaker pattern for failed providers
3. **Data Validation Layer**
```typescript
// libs/data-validation (NEW LIBRARY NEEDED)
- Price reasonableness checks
- Volume validation
- Timestamp validation
- Missing data detection
```
4. **Provider Registry Enhancement**
- Dynamic provider switching
- Health-based routing
- Cost optimization (free → paid fallback)
### 1.2 Raw Data Storage
**Storage Strategy**:
- **QuestDB**: Real-time market data (OHLCV, quotes)
- **MongoDB**: Provider responses, metadata, configurations
- **PostgreSQL**: Processed/clean data, trading records
**Schema Design**:
```sql
-- QuestDB Time-Series Tables
raw_quotes (timestamp, symbol, provider, bid, ask, last, volume)
raw_ohlcv (timestamp, symbol, provider, open, high, low, close, volume)
provider_health (timestamp, provider, latency, success_rate, error_rate)
-- MongoDB Collections
provider_responses: { provider, symbol, timestamp, raw_response, status }
data_quality_metrics: { symbol, date, completeness, accuracy, issues[] }
```
**Immediate Implementation**:
1. Enhance `libs/questdb-client` with streaming inserts
2. Add data retention policies
3. Implement data compression strategies
---
## 🧹 Phase 2: Data Processing & Quality Layer
### 2.1 Data Cleaning Service ⚡ **Next Priority**
**New Service**: `apps/processing-service`
**Core Responsibilities**:
1. **Data Normalization**
- Standardize timestamps (UTC)
- Normalize price formats
- Handle split/dividend adjustments
2. **Quality Checks**
- Outlier detection (price spikes, volume anomalies)
- Gap filling strategies
- Cross-provider validation
3. **Data Enrichment**
- Calculate derived metrics (returns, volatility)
- Add technical indicators
- Market session classification
**Library Enhancements Needed**:
```typescript
// libs/data-frame (ENHANCE EXISTING)
class MarketDataFrame {
// Add time-series specific operations
fillGaps(strategy: GapFillStrategy): MarketDataFrame;
detectOutliers(method: OutlierMethod): OutlierReport;
normalize(): MarketDataFrame;
calculateReturns(period: number): MarketDataFrame;
}
// libs/data-quality (NEW LIBRARY)
interface QualityMetrics {
completeness: number;
accuracy: number;
timeliness: number;
consistency: number;
issues: QualityIssue[];
}
```
### 2.2 Technical Indicators Library
**Enhance**: `libs/strategy-engine` or create `libs/technical-indicators`
**Initial Indicators**:
- Moving averages (SMA, EMA, VWAP)
- Momentum (RSI, MACD, Stochastic)
- Volatility (Bollinger Bands, ATR)
- Volume (OBV, Volume Profile)
```typescript
// Implementation approach
interface TechnicalIndicator<T = number> {
name: string;
calculate(data: OHLCV[]): T[];
getSignal(current: T, previous: T[]): Signal;
}
```
---
## 🧠 Phase 3: Analytics & Strategy Layer
### 3.1 Strategy Engine Enhancement
**Current**: Basic structure exists in `libs/strategy-engine`
**Enhancements Needed**:
1. **Strategy Framework**
```typescript
abstract class TradingStrategy {
abstract analyze(data: MarketData): StrategySignal[];
abstract getRiskParams(): RiskParameters;
backtest(historicalData: MarketData[]): BacktestResults;
}
```
2. **Signal Generation**
- Entry/exit signals
- Position sizing recommendations
- Risk-adjusted scores
3. **Strategy Types to Implement**:
- Mean reversion
- Momentum/trend following
- Statistical arbitrage
- Volume-based strategies
### 3.2 Backtesting Engine
**New Service**: Enhanced `apps/strategy-service`
**Features**:
- Historical simulation
- Performance metrics calculation
- Risk analysis
- Strategy comparison
---
## ⚡ Phase 4: Execution Layer
### 4.1 Portfolio Management
**Enhance**: `apps/portfolio-service`
**Core Features**:
- Position tracking
- Risk monitoring
- P&L calculation
- Margin management
### 4.2 Order Management
**New Service**: `apps/order-service`
**Responsibilities**:
- Order validation
- Execution routing
- Fill reporting
- Trade reconciliation
### 4.3 Risk Management
**New Library**: `libs/risk-engine`
**Risk Controls**:
- Position limits
- Drawdown limits
- Correlation limits
- Volatility scaling
---
## 📚 Library Improvements Roadmap
### Immediate (Phase 1-2)
1. **`libs/http`** ✅ **Current Priority**
- [ ] Rate limiting middleware
- [ ] Circuit breaker pattern
- [ ] Request/response caching
- [ ] Retry strategies with exponential backoff
2. **`libs/questdb-client`**
- [ ] Streaming insert optimization
- [ ] Batch insert operations
- [ ] Connection pooling
- [ ] Query result caching
3. **`libs/logger`** ✅ **Recently Updated**
- [x] Migrated to `getLogger()` pattern
- [ ] Performance metrics logging
- [ ] Structured trading event logging
4. **`libs/data-frame`**
- [ ] Time-series operations
- [ ] Financial calculations
- [ ] Memory optimization for large datasets
### Medium Term (Phase 3)
5. **`libs/cache`**
- [ ] Market data caching strategies
- [ ] Cache warming for frequently accessed symbols
- [ ] Distributed caching support
6. **`libs/config`**
- [ ] Strategy-specific configurations
- [ ] Dynamic configuration updates
- [ ] Environment-specific overrides
### Long Term (Phase 4+)
7. **`libs/vector-engine`**
- [ ] Market similarity analysis
- [ ] Pattern recognition
- [ ] Correlation analysis
---
## 🎯 Immediate Next Steps (Next 2 Weeks)
### Week 1: Data Provider Hardening
1. **Enhance HTTP Client** (`libs/http`)
- Implement rate limiting
- Add circuit breaker pattern
- Add comprehensive error handling
2. **Provider Reliability** (`apps/data-service`)
- Add health checks for all providers
- Implement fallback logic
- Add provider performance monitoring
3. **Data Validation**
- Create `libs/data-validation`
- Implement basic price/volume validation
- Add data quality metrics
### Week 2: Processing Foundation
1. **Start Processing Service** (`apps/processing-service`)
- Basic data cleaning pipeline
- Outlier detection
- Gap filling strategies
2. **QuestDB Optimization** (`libs/questdb-client`)
- Implement streaming inserts
- Add batch operations
- Optimize for time-series data
3. **Technical Indicators**
- Start `libs/technical-indicators`
- Implement basic indicators (SMA, EMA, RSI)
---
## 📊 Success Metrics
### Phase 1 Completion Criteria
- [ ] 99.9% data provider uptime
- [ ] <500ms average data latency
- [ ] Zero data quality issues for major symbols
- [ ] All providers monitored and health-checked
### Phase 2 Completion Criteria
- [ ] Automated data quality scoring
- [ ] Gap-free historical data for 100+ symbols
- [ ] Real-time technical indicator calculation
- [ ] Processing latency <100ms
### Phase 3 Completion Criteria
- [ ] 5+ implemented trading strategies
- [ ] Comprehensive backtesting framework
- [ ] Performance analytics dashboard
---
## 🚨 Risk Mitigation
### Data Risks
- **Provider Failures**: Multi-provider fallback strategy
- **Data Quality**: Automated validation and alerting
- **Rate Limits**: Smart request distribution
### Technical Risks
- **Scalability**: Horizontal scaling design
- **Latency**: Optimize critical paths early
- **Data Loss**: Comprehensive backup strategies
### Operational Risks
- **Monitoring**: Full observability stack (Grafana, Loki, Prometheus)
- **Alerting**: Critical issue notifications
- **Documentation**: Keep architecture docs current
---
## 💡 Innovation Opportunities
### Machine Learning Integration
- Predictive models for data quality
- Anomaly detection in market data
- Strategy parameter optimization
### Real-time Processing
- Stream processing with Kafka/Pulsar
- Event-driven architecture
- WebSocket data feeds
### Advanced Analytics
- Market microstructure analysis
- Alternative data integration
- Cross-asset correlation analysis
---
*This roadmap is a living document that will evolve as we learn and adapt. Focus remains on building solid foundations before adding complexity.*
**Next Review**: End of June 2025

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@ -19,112 +19,205 @@ export const proxyProvider: ProviderConfig = {
operations: {
'fetch-and-check': async (payload: { sources?: string[] }) => {
const { proxyService } = await import('./proxy.tasks');
const { queueManager } = await import('../services/queue.service');
await queueManager.drainQueue();
const proxies = await proxyService.fetchProxiesFromSources();
const proxiesCount = proxies.length;
// Get the actual proxies to create individual jobs
if (proxiesCount > 0) {
try {
const { queueManager } = await import('../services/queue.service');
if (proxies && proxies.length > 0) {
// Calculate delay distribution over 24 hours
const totalDelayMs = 24 * 60 * 60 * 1000; // 24 hours in milliseconds
const delayPerProxy = Math.floor(totalDelayMs / proxies.length);
if (proxiesCount === 0) {
logger.info('No proxies fetched, skipping job creation');
return { proxiesFetched: 0, batchJobsCreated: 0 };
}
try {
// Optimized batch size for 800k proxies
const batchSize = 200; // Process 200 proxies per batch job
const totalBatches = Math.ceil(proxies.length / batchSize);
const totalDelayMs = 24 * 60 * 60 * 1000; // 24 hours
const delayPerBatch = Math.floor(totalDelayMs / totalBatches);
logger.info('Creating proxy validation batch jobs', {
totalProxies: proxies.length,
batchSize,
totalBatches,
delayPerBatch: `${(delayPerBatch / 1000 / 60).toFixed(2)} minutes`,
estimatedCompletion: '24 hours'
});
// Process batches in chunks to avoid memory issues
const batchCreationChunkSize = 50; // Create 50 batch jobs at a time
let batchJobsCreated = 0;
for (let chunkStart = 0; chunkStart < totalBatches; chunkStart += batchCreationChunkSize) {
const chunkEnd = Math.min(chunkStart + batchCreationChunkSize, totalBatches);
// Create batch jobs in parallel for this chunk
const batchPromises = [];
for (let i = chunkStart; i < chunkEnd; i++) {
const startIndex = i * batchSize;
const endIndex = Math.min(startIndex + batchSize, proxies.length);
const batchProxies = proxies.slice(startIndex, endIndex);
const delay = i * delayPerBatch;
logger.info('Creating individual proxy validation jobs', {
proxyCount: proxies.length,
distributionPeriod: '24 hours',
delayPerProxy: `${(delayPerProxy / 1000 / 60).toFixed(2)} minutes`
const batchPromise = queueManager.addJob({
type: 'proxy-batch-validation',
service: 'proxy',
provider: 'proxy-service',
operation: 'process-proxy-batch',
payload: {
proxies: batchProxies,
batchIndex: i,
totalBatches,
source: 'fetch-and-check'
},
priority: 3
}, {
delay: delay,
jobId: `proxy-batch-${i}-${Date.now()}`
});
let queuedCount = 0;
for (let i = 0; i < proxies.length; i++) {
const proxy = proxies[i];
const delay = i * delayPerProxy;
try {
await queueManager.addJob({
type: 'proxy-validation',
service: 'proxy',
provider: 'proxy-service',
operation: 'check-proxy',
payload: {
proxy: proxy,
source: 'fetch-and-check',
autoTriggered: true,
batchIndex: i,
totalBatch: proxies.length
},
priority: 3
}, {
delay: delay
});
queuedCount++;
// Log progress every 100 jobs
if ((i + 1) % 100 === 0 || i === proxies.length - 1) {
logger.info('Proxy validation jobs queued progress', {
queued: i + 1,
total: proxies.length,
percentage: `${((i + 1) / proxies.length * 100).toFixed(1)}%`
});
}
} catch (error) {
logger.error('Failed to queue proxy validation job', {
proxy: `${proxy.host}:${proxy.port}`,
batchIndex: i,
error: error instanceof Error ? error.message : String(error)
});
} }
logger.info('Proxy validation jobs queuing completed', {
total: proxies.length,
successful: queuedCount,
failed: proxies.length - queuedCount,
totalDelay: `${(totalDelayMs / 1000 / 60 / 60).toFixed(1)} hours`,
avgDelayPerJob: `${(delayPerProxy / 1000 / 60).toFixed(2)} minutes`
});
return {
proxiesFetched: proxiesCount,
jobsQueued: queuedCount,
totalDelay: `${(totalDelayMs / 1000 / 60 / 60).toFixed(1)} hours`,
avgDelayPerJob: `${(delayPerProxy / 1000 / 60).toFixed(2)} minutes`
};
} else {
logger.warn('No proxies found to create validation jobs', {
proxiesFetched: proxiesCount
});
return {
proxiesFetched: proxiesCount,
jobsQueued: 0,
message: 'No cached proxies found'
};
batchPromises.push(batchPromise);
}
} catch (error) {
logger.error('Failed to create individual proxy validation jobs', {
proxiesCount,
error: error instanceof Error ? error.message : String(error)
// Wait for this chunk to complete
const results = await Promise.allSettled(batchPromises);
const successful = results.filter(r => r.status === 'fulfilled').length;
const failed = results.filter(r => r.status === 'rejected').length;
batchJobsCreated += successful;
logger.info('Batch chunk created', {
chunkStart: chunkStart + 1,
chunkEnd,
totalChunks: Math.ceil(totalBatches / batchCreationChunkSize),
successful,
failed,
totalCreated: batchJobsCreated,
progress: `${((chunkEnd / totalBatches) * 100).toFixed(1)}%`
});
return {
proxiesFetched: proxiesCount,
jobsQueued: 0,
error: error instanceof Error ? error.message : String(error)
}; }
} else { logger.info('No proxies fetched, skipping job creation');
// Small delay between chunks to prevent overwhelming Redis
if (chunkEnd < totalBatches) {
await new Promise(resolve => setTimeout(resolve, 100));
}
}
logger.info('All batch jobs creation completed', {
totalProxies: proxies.length,
batchJobsCreated,
totalBatches,
avgProxiesPerBatch: Math.floor(proxies.length / totalBatches),
estimatedDuration: '24 hours'
});
return {
proxiesFetched: 0,
jobsQueued: 0,
message: 'No proxies fetched'
proxiesFetched: proxiesCount,
batchJobsCreated,
totalBatches,
avgProxiesPerBatch: Math.floor(proxies.length / totalBatches)
};
} catch (error) {
logger.error('Failed to create batch jobs', {
proxiesCount,
error: error instanceof Error ? error.message : String(error)
});
throw error;
}
},
'process-proxy-batch': async (payload: {
proxies: ProxyInfo[],
batchIndex: number,
totalBatches: number,
source: string
}) => {
const { queueManager } = await import('../services/queue.service');
logger.info('Processing proxy batch', {
batchIndex: payload.batchIndex,
batchSize: payload.proxies.length,
totalBatches: payload.totalBatches,
progress: `${((payload.batchIndex + 1) / payload.totalBatches * 100).toFixed(2)}%`
});
const batchDelayMs = 15 * 60 * 1000; // 15 minutes per batch
const delayPerProxy = Math.floor(batchDelayMs / payload.proxies.length);
logger.info('Batch timing calculated', {
batchIndex: payload.batchIndex,
proxiesInBatch: payload.proxies.length,
batchDurationMinutes: 30,
delayPerProxySeconds: Math.floor(delayPerProxy / 1000),
delayPerProxyMs: delayPerProxy
});
// Use BullMQ's addBulk for better performance
const jobsToCreate = payload.proxies.map((proxy, i) => ({
name: 'proxy-validation',
data: {
type: 'proxy-validation',
service: 'proxy',
provider: 'proxy-service',
operation: 'check-proxy',
payload: {
proxy: proxy,
source: payload.source,
batchIndex: payload.batchIndex,
proxyIndexInBatch: i,
totalBatch: payload.totalBatches
},
priority: 2
},
opts: {
delay: i * delayPerProxy,
jobId: `proxy-${proxy.host}-${proxy.port}-batch${payload.batchIndex}-${Date.now()}-${i}`,
removeOnComplete: 3,
removeOnFail: 5
}
}));
try {
const jobs = await queueManager.addBulk(jobsToCreate);
logger.info('Batch processing completed successfully', {
batchIndex: payload.batchIndex,
totalProxies: payload.proxies.length,
jobsCreated: jobs.length,
batchDelay: '15 minutes',
progress: `${((payload.batchIndex + 1) / payload.totalBatches * 100).toFixed(2)}%`
});
return {
batchIndex: payload.batchIndex,
totalProxies: payload.proxies.length,
jobsCreated: jobs.length,
jobsFailed: 0
};
} catch (error) {
logger.error('Failed to create validation jobs for batch', {
batchIndex: payload.batchIndex,
batchSize: payload.proxies.length,
error: error instanceof Error ? error.message : String(error)
});
return {
batchIndex: payload.batchIndex,
totalProxies: payload.proxies.length,
jobsCreated: 0,
jobsFailed: payload.proxies.length
};
}
},
'check-proxy': async (payload: {
'check-proxy': async (payload: {
proxy: ProxyInfo,
source?: string,
batchIndex?: number,
proxyIndexInBatch?: number,
totalBatch?: number
}) => {
const { checkProxy } = await import('./proxy.tasks');
@ -132,7 +225,7 @@ export const proxyProvider: ProviderConfig = {
logger.debug('Checking individual proxy', {
proxy: `${payload.proxy.host}:${payload.proxy.port}`,
batchIndex: payload.batchIndex,
totalBatch: payload.totalBatch,
proxyIndex: payload.proxyIndexInBatch,
source: payload.source
});
@ -148,12 +241,13 @@ export const proxyProvider: ProviderConfig = {
return {
result: result,
batchInfo: {
index: payload.batchIndex,
batchIndex: payload.batchIndex,
proxyIndex: payload.proxyIndexInBatch,
total: payload.totalBatch,
source: payload.source
}
};
},
}
},
scheduledJobs: [

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@ -47,7 +47,7 @@ export class QueueService {
};
// Worker configuration
const workerCount = parseInt(process.env.WORKER_COUNT || '4');
const workerCount = parseInt(process.env.WORKER_COUNT || '5');
const concurrencyPerWorker = parseInt(process.env.WORKER_CONCURRENCY || '20');
this.logger.info('Connecting to Redis/Dragonfly', connection);
@ -180,6 +180,10 @@ export class QueueService {
throw error;
}
}
async addBulk(jobs: any[]) : Promise<any[]> {
return await this.queue.addBulk(jobs)
}
private setupEventListeners() {
this.queueEvents.on('completed', (job) => {
this.logger.info('Job completed', { id: job.jobId });
@ -396,6 +400,13 @@ export class QueueService {
delayed: delayed.length
};
}
async drainQueue() {
if (!this.isInitialized) {
await this.queue.drain()
}
}
async getQueueStatus() {
if (!this.isInitialized) {
throw new Error('Queue service not initialized. Call initialize() first.');
@ -412,12 +423,14 @@ export class QueueService {
}
};
}
getWorkerCount() {
if (!this.isInitialized) {
return 0;
}
return this.workers.length;
}
getRegisteredProviders() {
return providerRegistry.getProviders().map(({ key, config }) => ({
key,

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@ -0,0 +1,24 @@
{
"name": "@stock-bot/data-adjustments",
"version": "1.0.0",
"description": "Stock split and dividend adjustment utilities for market data",
"type": "module",
"main": "dist/index.js",
"types": "dist/index.d.ts",
"scripts": {
"build": "tsc",
"test": "bun test",
"test:watch": "bun test --watch"
},
"dependencies": {
"@stock-bot/types": "*",
"@stock-bot/logger": "*"
},
"devDependencies": {
"typescript": "^5.4.5",
"bun-types": "^1.1.12"
},
"peerDependencies": {
"typescript": "^5.0.0"
}
}