Create Memory-Efficient Table1 Blueprint Object

Creates an optimized blueprint object with sparse storage using R environments for hash-table like performance. Only populated cells consume memory, providing significant memory savings for typical sparse table structures.

Usage

Table1Blueprint(nrows, ncols)

Arguments

nrows

Integer specifying the number of rows in the final table. Must be a positive integer

ncols

Integer specifying the number of columns in the final table. Must be a positive integer

Value

An object of class "table1_blueprint" with components:

• cells: Environment with hash-table storage for cells

• nrows: Number of rows

• ncols: Number of columns

• row_names: Character vector of row identifiers

• col_names: Character vector of column headers

• metadata: List containing structural information

Details

The optimized blueprint uses environment-based sparse storage instead of pre-allocating all cells. Benefits include:

• Memory usage scales with actual content, not table dimensions

• O(1) hash-table lookup for cell access

• Automatic garbage collection of unused cells

• Support for very large sparse tables

See also

Cell, validate_table1_blueprint

Examples

# Small table - minimal memory usage
bp_small <- Table1Blueprint(5, 3)
bp_small[1, 1] <- Cell(type = "content", content = "Variable")

# Large sparse table - still efficient
bp_large <- Table1Blueprint(1000, 100) # Only uses memory for metadata