to_dataframe, Interval.duration, and sticky timeline metadata

[ashenfad]

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[Copilot]

Pull request overview

This PR adds DataFrame conversion capabilities, introduces an Interval.duration property, and implements sticky timeline metadata for preserving calendar source information.

• Adds to_dataframe() function with intelligent column ordering and formatting for converting intervals to pandas DataFrames
• Implements Interval.duration property returning duration in seconds or None for unbounded intervals
• Adds metadata parameter to MemoryTimeline that applies container-level metadata (e.g., calendar_name) to new events

Reviewed changes

Copilot reviewed 9 out of 9 changed files in this pull request and generated 2 comments.

Show a summary per file

File	Description
tests/test_dataframe.py	Comprehensive test suite for to_dataframe() function covering basic intervals, ICalEvent formatting, column filtering, and duration formatting
pyproject.toml	Adds pandas>=2.0 as optional dependency under both dev and pandas extras
docs/API.md	Documents new DataFrame helpers section and Interval.duration property, plus updates import path in example
calgebra/mutable/memory.py	Adds metadata parameter to MemoryTimeline for container-level metadata that fills in missing values on new events
calgebra/interval.py	Adds duration property to Interval class returning end - start in seconds
calgebra/ical.py	Extracts calendar_name from X-WR-CALNAME and passes it as container metadata to MemoryTimeline
calgebra/docs/API.md	Duplicate documentation updates matching docs/API.md changes
calgebra/dataframe.py	New module implementing to_dataframe() with timezone-aware formatting, column ordering, and metadata handling
calgebra/init.py	Exports new to_dataframe function and additional ical module components

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