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//! Monthly work summary calculation and formatting system.
//!
//! Provides comprehensive functionality for calculating, processing, and formatting
//! monthly work summaries. Handles the complex business logic of combining actual
//! work data with company rest days to produce complete monthly reports.
//!
//! ## Features
//!
//! - **Daily Summary Aggregation**: Combines work duration and productivity metrics
//! - **Rest Day Integration**: Incorporates company holidays and weekends
//! - **Statistical Calculations**: Computes totals, averages, and productivity metrics
//! - **Flexible Formatting**: Provides multiple output formats for different use cases
//! - **Report Generation**: Powers monthly reports and export functionality
//!
//! ## Usage
//!
//! ```rust,no_run
//! use kasl::libs::summary::{DailySummary, SummaryCalculator, SummaryFormatter};
//! use chrono::{Duration, NaiveDate};
//! use std::collections::HashSet;
//!
//! let summaries = vec![
//! DailySummary {
//! date: NaiveDate::from_ymd_opt(2025, 8, 11).unwrap(),
//! duration: Duration::hours(8),
//! productivity: 85.5,
//! },
//! ];
//!
//! let rest_dates = HashSet::new();
//! let (processed, total, average) = summaries
//! .add_rest_dates(rest_dates, Duration::hours(8))
//! .calculate_totals();
//! ```
use crateformat_duration;
use ;
use ;
/// Represents a complete work summary for a single calendar day.
///
/// This structure encapsulates all the key metrics needed to understand
/// work performance on a given day, including both time-based and
/// productivity-based measurements. It serves as the fundamental unit
/// for monthly reporting and analysis.
///
/// ## Data Components
///
/// ### Duration Tracking
/// The duration represents net productive work time:
/// - **Gross Time**: Total presence time (workday start to end)
/// - **Pause Time**: All break periods during the day
/// - **Net Time**: Gross time minus pause time (stored in duration field)
///
/// ### Productivity Metrics
/// Productivity is calculated as a percentage representing work efficiency:
/// - **Formula**: (Net Work Time / Gross Presence Time) × 100
/// - **Range**: 0.0 to 100.0 (theoretical maximum)
/// - **Typical Values**: 70-90% for most office work patterns
/// - **Factors**: Affected by meeting frequency, break patterns, and work type
///
/// ## Use Cases
///
/// ### Individual Analysis
/// - Daily productivity tracking and improvement
/// - Work pattern analysis and optimization
/// - Break frequency and duration analysis
///
/// ### Organizational Reporting
/// - Monthly time sheets and hour summaries
/// - Productivity benchmarking across teams
/// - Resource allocation and planning data
/// - Compliance with work hour regulations
///
/// ### External Integration
/// - Payroll system integration
/// - Project time allocation
/// - Client billing and invoicing
/// - Performance review documentation
/// Trait for processing and enhancing collections of daily summaries.
///
/// This trait provides the core business logic for preparing monthly
/// reports by integrating actual work data with organizational calendar
/// information. It ensures comprehensive coverage of all calendar days
/// and provides statistical analysis capabilities.
///
/// ## Design Philosophy
///
/// The trait follows a functional programming approach with method chaining:
/// ```rust,no_run
/// use kasl::libs::summary::{DailySummary, SummaryCalculator};
/// use chrono::Duration;
/// use std::collections::HashSet;
///
/// let summaries: Vec<DailySummary> = vec![];
/// let company_holidays = HashSet::new();
/// let default_hours = Duration::hours(8);
///
/// let result = summaries
/// .add_rest_dates(company_holidays, default_hours)
/// .calculate_totals();
/// ```
///
/// This design enables:
/// - **Composability**: Methods can be chained for complex transformations
/// - **Immutability**: Each method returns a new collection
/// - **Readability**: Clear sequence of data processing steps
/// - **Testability**: Each transformation can be tested independently
///
/// ## Implementation Strategy
///
/// Implementations should handle:
/// - **Data Completeness**: Ensure all calendar days are represented
/// - **Duplicate Prevention**: Avoid duplicate entries for the same date
/// - **Statistical Accuracy**: Provide meaningful aggregate calculations
/// - **Performance**: Efficient processing of month-long datasets