mirror of
https://github.com/Xe138/AI-Trader.git
synced 2026-04-01 17:17:24 -04:00
feat: implement date range API and on-demand downloads (WIP phase 2)
Phase 2 progress - API integration complete. API Changes: - Replace date_range (List[str]) with start_date/end_date (str) - Add automatic end_date defaulting to start_date for single day - Add date format validation - Integrate PriceDataManager for on-demand downloads - Add rate limit handling (trusts provider, no pre-config) - Validate date ranges with configurable max days (MAX_SIMULATION_DAYS) New Modules: - api/date_utils.py - Date validation and expansion utilities - scripts/migrate_price_data.py - Migration script for merged.jsonl API Flow: 1. Validate date range (start <= end, max 30 days, not future) 2. Check missing price data coverage 3. Download missing data if AUTO_DOWNLOAD_PRICE_DATA=true 4. Priority-based download (maximize date completion) 5. Create job with available trading dates 6. Graceful handling of partial data (rate limits) Configuration: - AUTO_DOWNLOAD_PRICE_DATA (default: true) - MAX_SIMULATION_DAYS (default: 30) - No rate limit configuration needed Still TODO: - Update tools/price_tools.py to read from database - Implement simulation run tracking - Update .env.example - Comprehensive testing - Documentation updates Breaking Changes: - API request format changed (date_range -> start_date/end_date) - This completes v0.3.0 preparation
This commit is contained in:
93
api/date_utils.py
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93
api/date_utils.py
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"""
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Date range utilities for simulation date management.
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This module provides:
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- Date range expansion
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- Date range validation
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- Trading day detection
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"""
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import os
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from datetime import datetime, timedelta
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from typing import List
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def expand_date_range(start_date: str, end_date: str) -> List[str]:
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"""
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Expand date range into list of all dates (inclusive).
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Args:
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start_date: Start date (YYYY-MM-DD)
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end_date: End date (YYYY-MM-DD)
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Returns:
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Sorted list of dates in range
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Raises:
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ValueError: If dates are invalid or start > end
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"""
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start = datetime.strptime(start_date, "%Y-%m-%d")
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end = datetime.strptime(end_date, "%Y-%m-%d")
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if start > end:
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raise ValueError(f"start_date ({start_date}) must be <= end_date ({end_date})")
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dates = []
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current = start
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while current <= end:
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dates.append(current.strftime("%Y-%m-%d"))
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current += timedelta(days=1)
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return dates
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def validate_date_range(
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start_date: str,
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end_date: str,
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max_days: int = 30
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) -> None:
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"""
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Validate date range for simulation.
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Args:
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start_date: Start date (YYYY-MM-DD)
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end_date: End date (YYYY-MM-DD)
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max_days: Maximum allowed days in range
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Raises:
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ValueError: If validation fails
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"""
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# Parse dates
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try:
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start = datetime.strptime(start_date, "%Y-%m-%d")
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end = datetime.strptime(end_date, "%Y-%m-%d")
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except ValueError as e:
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raise ValueError(f"Invalid date format: {e}")
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# Check order
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if start > end:
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raise ValueError(f"start_date ({start_date}) must be <= end_date ({end_date})")
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# Check range size
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days = (end - start).days + 1
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if days > max_days:
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raise ValueError(
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f"Date range too large: {days} days (max: {max_days}). "
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f"Reduce range or increase MAX_SIMULATION_DAYS."
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)
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# Check not in future
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today = datetime.now().date()
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if end.date() > today:
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raise ValueError(f"end_date ({end_date}) cannot be in the future")
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def get_max_simulation_days() -> int:
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"""
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Get maximum simulation days from environment.
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Returns:
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Maximum days allowed in simulation range
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"""
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return int(os.getenv("MAX_SIMULATION_DAYS", "30"))
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126
api/main.py
126
api/main.py
@@ -9,6 +9,7 @@ Provides endpoints for:
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"""
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import logging
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import os
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from typing import Optional, List, Dict, Any
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from datetime import datetime
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from pathlib import Path
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@@ -20,6 +21,8 @@ from pydantic import BaseModel, Field, field_validator
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from api.job_manager import JobManager
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from api.simulation_worker import SimulationWorker
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from api.database import get_db_connection
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from api.price_data_manager import PriceDataManager
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from api.date_utils import validate_date_range, expand_date_range, get_max_simulation_days
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import threading
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import time
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@@ -29,23 +32,29 @@ logger = logging.getLogger(__name__)
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# Pydantic models for request/response validation
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class SimulateTriggerRequest(BaseModel):
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"""Request body for POST /simulate/trigger."""
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date_range: List[str] = Field(..., min_length=1, description="List of trading dates (YYYY-MM-DD)")
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start_date: str = Field(..., description="Start date for simulation (YYYY-MM-DD)")
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end_date: Optional[str] = Field(None, description="End date for simulation (YYYY-MM-DD). If not provided, simulates single day.")
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models: Optional[List[str]] = Field(
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None,
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description="Optional: List of model signatures to simulate. If not provided, uses enabled models from config."
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)
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@field_validator("date_range")
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@field_validator("start_date", "end_date")
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@classmethod
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def validate_date_range(cls, v):
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def validate_date_format(cls, v):
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"""Validate date format."""
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for date in v:
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try:
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datetime.strptime(date, "%Y-%m-%d")
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except ValueError:
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raise ValueError(f"Invalid date format: {date}. Expected YYYY-MM-DD")
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if v is None:
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return v
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try:
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datetime.strptime(v, "%Y-%m-%d")
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except ValueError:
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raise ValueError(f"Invalid date format: {v}. Expected YYYY-MM-DD")
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return v
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def get_end_date(self) -> str:
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"""Get end date, defaulting to start_date if not provided."""
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return self.end_date or self.start_date
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class SimulateTriggerResponse(BaseModel):
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"""Response body for POST /simulate/trigger."""
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@@ -114,13 +123,12 @@ def create_app(
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"""
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Trigger a new simulation job.
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Creates a job with dates and models from config file.
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If models not specified in request, uses enabled models from config.
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Job runs asynchronously in background thread.
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Validates date range, downloads missing price data if needed,
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and creates job with available trading dates.
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Raises:
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HTTPException 400: If another job is already running or config invalid
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HTTPException 422: If request validation fails
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HTTPException 400: Validation errors, running job, or invalid dates
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HTTPException 503: Price data download failed
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"""
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try:
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# Use config path from app state
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@@ -133,6 +141,13 @@ def create_app(
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detail=f"Server configuration file not found: {config_path}"
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)
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# Get end date (defaults to start_date for single day)
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end_date = request.get_end_date()
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# Validate date range
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max_days = get_max_simulation_days()
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validate_date_range(request.start_date, end_date, max_days=max_days)
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# Determine which models to run
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import json
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with open(config_path, 'r') as f:
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@@ -155,6 +170,67 @@ def create_app(
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detail="No enabled models found in config. Either enable models in config or specify them in request."
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)
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# Check price data and download if needed
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auto_download = os.getenv("AUTO_DOWNLOAD_PRICE_DATA", "true").lower() == "true"
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price_manager = PriceDataManager(db_path=app.state.db_path)
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# Check what's missing
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missing_coverage = price_manager.get_missing_coverage(
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request.start_date,
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end_date
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)
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download_info = None
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# Download missing data if enabled
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if any(missing_coverage.values()):
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if not auto_download:
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raise HTTPException(
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status_code=400,
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detail=f"Missing price data for {len(missing_coverage)} symbols and auto-download is disabled. "
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f"Enable AUTO_DOWNLOAD_PRICE_DATA or pre-populate data."
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)
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logger.info(f"Downloading missing price data for {len(missing_coverage)} symbols")
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requested_dates = set(expand_date_range(request.start_date, end_date))
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download_result = price_manager.download_missing_data_prioritized(
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missing_coverage,
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requested_dates
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)
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if not download_result["success"]:
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raise HTTPException(
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status_code=503,
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detail="Failed to download any price data. Check ALPHAADVANTAGE_API_KEY."
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)
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download_info = {
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"symbols_downloaded": len(download_result["downloaded"]),
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"symbols_failed": len(download_result["failed"]),
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"rate_limited": download_result["rate_limited"]
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}
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logger.info(
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f"Downloaded {len(download_result['downloaded'])} symbols, "
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f"{len(download_result['failed'])} failed, rate_limited={download_result['rate_limited']}"
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)
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# Get available trading dates (after potential download)
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available_dates = price_manager.get_available_trading_dates(
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request.start_date,
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end_date
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)
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if not available_dates:
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raise HTTPException(
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status_code=400,
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detail=f"No trading dates with complete price data in range "
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f"{request.start_date} to {end_date}. "
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f"All symbols must have data for a date to be tradeable."
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)
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job_manager = JobManager(db_path=app.state.db_path)
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# Check if can start new job
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@@ -164,10 +240,10 @@ def create_app(
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detail="Another simulation job is already running or pending. Please wait for it to complete."
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)
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# Create job
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# Create job with available dates
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job_id = job_manager.create_job(
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config_path=config_path,
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date_range=request.date_range,
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date_range=available_dates,
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models=models_to_run
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)
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@@ -180,15 +256,27 @@ def create_app(
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thread = threading.Thread(target=run_worker, daemon=True)
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thread.start()
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logger.info(f"Triggered simulation job {job_id}")
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logger.info(f"Triggered simulation job {job_id} with {len(available_dates)} dates")
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return SimulateTriggerResponse(
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# Build response message
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message = f"Simulation job created with {len(available_dates)} trading dates"
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if download_info and download_info["rate_limited"]:
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message += " (rate limit reached - partial data)"
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response = SimulateTriggerResponse(
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job_id=job_id,
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status="pending",
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total_model_days=len(request.date_range) * len(models_to_run),
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message=f"Simulation job {job_id} created and started with {len(models_to_run)} models"
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total_model_days=len(available_dates) * len(models_to_run),
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message=message
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)
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# Add download info if we downloaded
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if download_info:
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# Note: Need to add download_info field to response model
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logger.info(f"Download info: {download_info}")
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return response
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except HTTPException:
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raise
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except ValueError as e:
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