105 lines
3.8 KiB
Markdown
105 lines
3.8 KiB
Markdown
# 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
|