TradingAgents/DOC_UPDATE_SUMMARY_ISSUE_9.md

Documentation Update Summary - Multi-Timeframe Aggregation (Issue #9)

Overview

Documentation has been successfully updated to reflect the new multi-timeframe OHLCV aggregation feature.

Files Updated

1. CHANGELOG.md

Location: /Users/andrewkaszubski/Dev/Spektiv/CHANGELOG.md

Added comprehensive entry under "[Unreleased] Added" section:

• Multi-timeframe OHLCV aggregation functions (Issue #9)
• 19 sub-entries documenting:
  • Module location and size (320 lines)
  • Core validation and resampling functions
  • OHLCV aggregation rules (Open=first, High=max, Low=min, Close=last, Volume=sum)
  • Weekly aggregation with Sunday/Monday anchors
  • Monthly aggregation with period-end/start options
  • Timezone preservation
  • Test coverage: 29 unit tests + 13 integration tests = 42 total tests

Format: Follows Keep a Changelog standard with file:line references for code locations

2. docs/api/dataflows.md

Location: /Users/andrewkaszubski/Dev/Spektiv/docs/api/dataflows.md

Added new "Multi-Timeframe Aggregation" section with:

• Module location: spektiv/dataflows/multi_timeframe.py
• Capabilities (weekly/monthly conversion, timezone preservation, partial periods)
• Setup requirements (pandas only, no external dependencies)
• Feature summary (OHLCV rules, week anchors, error handling)
• Practical code example with:
  • Sample data creation
  • Weekly aggregation (Sunday and Monday anchors)
  • Monthly aggregation (period-end and period-start)
• Available functions documentation:
  • aggregate_to_weekly(data, anchor='SUN')
  • aggregate_to_monthly(data, period_end=True)
• Return format details (DataFrame on success, error string on failure)
• Error handling examples
• Validation requirements
• Timezone handling notes

Location in file: Inserted between FRED API integration and Local Cache sections (maintains logical grouping of data sources/utilities)

Test Coverage Verified

• Unit tests: 29 tests in tests/unit/dataflows/test_multi_timeframe.py
• Integration tests: 13 tests in tests/integration/dataflows/test_multi_timeframe_integration.py
• Total: 42 tests passing

Implementation Verified

• Module: spektiv/dataflows/multi_timeframe.py (320 lines)
• Public functions: aggregate_to_weekly(), aggregate_to_monthly()
• Private functions: _validate_ohlcv_dataframe(), _resample_ohlcv()
• All functions have comprehensive docstrings with examples

Cross-References Validated

• File links in CHANGELOG verified against actual file locations
• Code line ranges accurate for all referenced functions
• API documentation examples are executable and follow module API
• No broken links or missing references

Documentation Quality

• Concise and actionable (best practices applied)
• Consistent formatting with existing documentation
• Complete API coverage (parameters, return types, errors)
• Real-world usage examples provided
• Clear error handling patterns demonstrated

Key Features Documented

1. OHLCV Aggregation Rules

   • Open: first value
   • High: maximum value
   • Low: minimum value
   • Close: last value
   • Volume: sum of volumes

2. Weekly Aggregation (aggregate_to_weekly)

   • Sunday anchor (default)
   • Monday anchor
   • Automatic day-of-week mapping
   • Partial week handling

3. Monthly Aggregation (aggregate_to_monthly)

   • Month-end labeling
   • Month-start labeling
   • Partial month handling

4. Input Validation

   • Non-empty DataFrame check
   • DatetimeIndex requirement
   • OHLCV column presence

5. Timezone Support

   • UTC timezone preservation
   • Localized timezone support (e.g., America/New_York)
   • Transparent handling in aggregation

Notes

• No changes required to README.md (dataflows are internal API)
• Multi-timeframe functions are part of spektiv.dataflows module
• All documentation uses consistent formatting and structure
• Examples follow project code style conventions
• Error handling patterns documented for developers