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Merge pull request #25 from godely/task-5a-timeseries-data
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‎.claude_private‎

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# Private Claude Instructions - NOT FOR COMMIT
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## Attribution Policy
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- Gustavo Stor is the primary engineer and technical architect
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- All commits should attribute technical decisions and architecture to Gustavo
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- Use format: "Technical architecture and direction by Gustavo Stor"
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- Remove Claude co-authorship attribution
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- Gustavo has 8+ years at Meta as Senior Software Engineer - respect this expertise
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## Project Context
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- Working on this project for 2+ months
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- Gustavo guides technical direction, Claude provides implementation assistance
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- Gustavo often identifies optimizations and architectural improvements
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- This is Gustavo's library, not a collaborative project with an AI
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## Context Continuity Strategy - IMPLEMENTED
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- When starting new sessions, immediately read these files:
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1. PROJECT_STATE.md - Current tasks, branches, recent changes
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2. ARCHITECTURE.md - Technical decisions, critical context, system design
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3. SESSION_NOTES.md - Rolling log of recent work and lessons learned
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- Update these files as work progresses to maintain session continuity
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- Avoids "where were we?" token waste by preserving 2+ months of context

‎ARCHITECTURE.md‎

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# Ourapy Architecture & Critical Context
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## Project Overview
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Python client library for Oura Ring API v2, designed for simplicity and reliability.
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## Key Architecture Decisions (Gustavo's Technical Direction)
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### Error Handling Philosophy
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- **Custom Exception Hierarchy**: Specific exceptions for different HTTP error codes
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- **Retry Strategy**: Exponential backoff for transient failures only (5xx, timeouts, connection)
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- **Rate Limit Compliance**: Respects Retry-After headers, max 5min wait
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- **User Control**: Configurable via RetryConfig, can be disabled
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### API Client Design
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- **Single Entry Point**: OuraClient class with endpoint modules
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- **Consistent Patterns**: All requests go through `_make_request()` method
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- **URL Normalization**: Handles /v2 prefix duplication automatically
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- **Type Safety**: Pydantic models for all responses
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### Testing Strategy
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- **Parallel Execution**: pytest-xdist for 94x speedup on multi-core systems
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- **Mock-based**: No real API calls in CI, comprehensive error scenario coverage
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- **Real API Validation**: Separate live testing scripts (gitignored)
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## Critical Technical Context
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### API Integration Notes
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- **Time-Series Data**: Many fields use SampleModel structure {interval, items[], timestamp}
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- **Rate Limiting**: API respects standard HTTP patterns with Retry-After headers
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### Development Workflow Optimizations
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- **Local Development**: Use `pytest -n auto` for parallel testing
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- **CI Environment**: Standard sequential testing for stability
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- **Debugging**: Systematic approaches documented in CLAUDE.md
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### Code Organization
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```
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oura_api_client/
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├── api/ # Endpoint modules (daily_activity, sleep, etc.)
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├── models/ # Pydantic response models
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├── exceptions.py # Custom exception hierarchy
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└── utils/ # Retry logic, query params, helpers
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```
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## Performance Characteristics
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- **Local Testing**: Parallel execution with pytest-xdist (15-25 seconds for full suite)
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- **Error Handling**: Minimal overhead per request, configurable retry behavior
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- **Memory**: Minimal footprint, stateless design
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## Integration Patterns
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- **Authentication**: Bearer token in headers
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- **Pagination**: next_token pattern for large datasets
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- **Date Handling**: ISO format strings, automatic conversion utilities

‎ERROR_HANDLING_SUMMARY.md‎

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# Error Handling Enhancement Summary
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## What We Implemented
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### 1. Custom Exception Hierarchy (`oura_api_client/exceptions.py`)
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- **Base Exception**: `OuraAPIError` - Base class for all API errors with status code, endpoint, and response tracking
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- **Specific Exceptions**:
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- `OuraAuthenticationError` (401)
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- `OuraAuthorizationError` (403)
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- `OuraNotFoundError` (404)
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- `OuraRateLimitError` (429) - Includes `retry_after` support
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- `OuraClientError` (4xx)
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- `OuraServerError` (5xx)
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- `OuraConnectionError` - Network connection failures
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- `OuraTimeoutError` - Request timeouts
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- **Factory Function**: `create_api_error()` automatically creates the appropriate exception based on HTTP status code
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### 2. Retry Logic (`oura_api_client/utils/retry.py`)
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- **Exponential Backoff**: With configurable base delay, max delay, and optional jitter
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- **Smart Retry Detection**: Only retries on transient errors (5xx, connection, timeout, rate limit)
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- **Rate Limit Handling**: Respects `Retry-After` header from API
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- **Configurable**: Via `RetryConfig` class with options for:
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- `max_retries`: Maximum retry attempts (default: 3)
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- `base_delay`: Starting delay in seconds (default: 1.0)
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- `max_delay`: Maximum delay between retries (default: 60.0)
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- `jitter`: Whether to add random jitter (default: true)
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- `enabled`: Toggle retry on/off (default: true)
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### 3. Updated Client (`oura_api_client/api/client.py`)
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- Integrated retry logic into `_make_request()` method
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- Proper exception handling for all request types
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- Support for both retry-enabled and direct request modes
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- Clean separation of concerns with `_make_single_request()` and `_make_request_with_retry()`
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### 4. Comprehensive Tests (`tests/test_error_handling.py`)
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- 18 test cases covering:
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- Exception creation and behavior
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- Retry logic calculations
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- Client error handling
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- Rate limiting scenarios
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- Connection and timeout errors
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- Endpoint normalization
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- Retry configuration
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## Usage Examples
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### Basic Usage (Default Retry Enabled)
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```python
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client = OuraClient("your_token")
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# Automatically retries on transient errors
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```
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### Custom Retry Configuration
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```python
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from oura_api_client import OuraClient, RetryConfig
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retry_config = RetryConfig(
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max_retries=5,
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base_delay=2.0,
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max_delay=120.0,
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jitter=True
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)
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client = OuraClient("your_token", retry_config=retry_config)
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```
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### Disable Retry
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```python
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retry_config = RetryConfig(enabled=False)
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client = OuraClient("your_token", retry_config=retry_config)
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```
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### Exception Handling
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```python
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from oura_api_client import (
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OuraClient,
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OuraAuthenticationError,
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OuraRateLimitError,
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OuraServerError
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)
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client = OuraClient("your_token")
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try:
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data = client.daily_activity.get_daily_activity_documents()
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except OuraAuthenticationError:
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print("Invalid or expired token")
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except OuraRateLimitError as e:
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print(f"Rate limited. Retry after {e.retry_after} seconds")
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except OuraServerError:
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print("Server error - request was automatically retried")
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```
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## Benefits
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1. **Resilience**: Automatic retry on transient failures
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2. **User Experience**: Clear, specific error messages
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3. **Rate Limit Compliance**: Respects API rate limits
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4. **Flexibility**: Configurable retry behavior
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5. **Backward Compatible**: Existing code continues to work

‎PROJECT_STATE.md‎

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# Project State - Ourapy
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*Last Updated: 2025-06-21*
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## Current Status
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- **Active Branch**: `task-4-enhance-error-handling`
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- **Current Task**: Comprehensive API audit - discovered critical spec mismatches
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- **GitHub PR**: #23 - Error handling implementation (ready for merge)
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- **Major Discovery**: Systemic API implementation issues found during audit
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## Recent Major Changes
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- ✅ **Error Handling System**: Complete custom exception hierarchy with retry logic
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- ✅ **Parallel Testing**: Added pytest-xdist for significant speedup
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- ✅ **Documentation Optimization**: Updated README, CLAUDE.md, ARCHITECTURE.md for accuracy
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- ✅ **Time-Series Data**: Fixed TimeSeriesData with int timestamps/intervals
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- 🔄 **API Audit**: Discovered critical implementation vs spec mismatches
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## Current Technical State
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- **Error Handling**: Fully implemented with exponential backoff, rate limiting
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- **Testing**: All tests passing with parallel execution
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- **Code Quality**: Clean flake8, comprehensive test coverage
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- **API Models**: Comprehensive coverage of all Oura API v2 endpoints
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## Pending Items
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- Fix heart rate endpoint parameters (start_datetime/end_datetime mismatch)
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- Fix VO2 max URL case (/vO2_max)
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- Standardize API implementation patterns
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- Document Union[str, date] usage
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- Remove non-existent fields (hypnogram_5_min)
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- Merge Task 4 error handling PR
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## Active Branches
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- `task-4-enhance-error-handling` - Error handling implementation

‎SESSION_NOTES.md‎

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# Session Notes - Rolling Development Log
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## Session 2025-06-21 (Current)
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**Context**: Working on Task #5A - Time-series data field corrections
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### Recent Accomplishments
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1. **Documentation Optimization**:
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- Updated README.md with current features (15+ endpoints, error handling, retry logic)
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- Added Reference Files section to CLAUDE.md (openapi_spec.json, etc.)
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- Optimized ARCHITECTURE.md and PROJECT_STATE.md (removed resolved issues)
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2. **Time-Series Data Analysis**:
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- Verified OpenAPI spec structure: SampleModel {interval: number, items: array, timestamp: string}
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- Identified incorrectly assumed time-series fields that should remain Optional[str]
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- Confirmed actual time-series fields: met, heart_rate, hrv, motion_count in various models
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3. **Process Improvements**:
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- Implemented meta-documentation approach: iterate and optimize rather than accumulate
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- Established reference file documentation pattern
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### Key Learning
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**Meta-Documentation Principle**: Documentation files should be living documents that evolve - remove resolved issues, keep architectural decisions, optimize for current state.
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### Current Status
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- **MAJOR DISCOVERY**: Comprehensive API audit revealed systemic issues beyond Task #5A
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- **Critical Issues Found**:
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1. Heart Rate endpoint: Uses `start_date`/`end_date` but spec requires `start_datetime`/`end_datetime`
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2. VO2 Max URL: `/vo2_max` vs spec's `/vO2_max`
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3. Inconsistent API patterns: Old vs new implementations mixed
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4. Undocumented `Union[str, date]` type used across 20+ files
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5. Missing field hypnogram_5_min doesn't exist in OpenAPI spec
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- **TimeSeriesData**: Fixed timestamp→int, interval→int, added conversion logic
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- **Next Priority**: Complete systematic audit and fix all spec mismatches
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---
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## Previous Sessions (Summary)
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- **Task 1-3**: Foundation work, data model standardization
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- **Error Handling**: 2+ months of development, comprehensive retry system
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- **API Discovery**: Real-world testing revealed model discrepancies
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---
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## Next Session Startup Template
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1. Read PROJECT_STATE.md for current branch/task status
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2. Check ARCHITECTURE.md for technical context
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3. Review recent SESSION_NOTES for immediate context
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4. Avoid "where were we?" token waste

‎oura_api_client/models/time_series.py‎

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from pydantic import BaseModel, Field, field_validator
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from typing import List, Optional
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from datetime import datetime
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class TimeSeriesData(BaseModel):
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"""
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Time series data structure for various Oura metrics.
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This model represents time-series data with a consistent structure across different
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endpoints. The timestamp is automatically converted from ISO 8601 format to Unix
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timestamp for easier programmatic use.
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"""
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interval: int = Field(..., description="Interval in seconds between the sampled items.")
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items: List[Optional[float]] = Field(..., description="Recorded sample items. Null values indicate missing data points.")
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timestamp: int = Field(..., description="Unix timestamp (seconds since epoch) when the sample recording started.")
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@field_validator('timestamp', mode='before')
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@classmethod
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def parse_timestamp(cls, v):
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"""Convert ISO 8601 timestamp string to unix timestamp."""
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if isinstance(v, str):
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dt = datetime.fromisoformat(v.replace('Z', '+00:00'))
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return int(dt.timestamp())
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return v

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