lazily-sliced 0.1.0a0

A memory-efficient Python sequence wrapper that applies slicing operations lazily, deferring data access until elements are actually needed.

lazily-sliced

A memory-efficient Python sequence wrapper that applies slicing operations lazily, deferring data access until elements are actually needed.

Features

• Zero-copy slicing: Avoids immediate data duplication when slicing sequences
• Full Sequence interface: Implements all collections.abc.Sequence operations
• Portable: Python 2 & 3 compatible, no dependencies
• Memory efficient: Uses __slots__ and lazy evaluation
• Composable: Handles nested slicing operations efficiently

Installation

pip install lazily-sliced

Usage

from lazily_sliced import LazilySliced

# Create from any sequence
data = list(range(1000))
lazy = LazilySliced(data, slice(100, 200))

# Standard sequence operations work
print(len(lazy))  # 100
print(lazy[10])   # 110
print(105 in lazy) # True

# Supports nested slicing
subset = lazy[10:20:2]
print(subset) # LazilySliced([110, 112, 114, 116, 118])
for item in lazy:
    print(item)

When to Use

Ideal for:

• Working with large sequences where you need small slices
• Memory-constrained environments
• Chaining multiple slicing operations
• Cases where immediate data copying is expensive

Performance Characteristics

Operation	Time Complexity	Notes
len()	O(1)
Index access	O(1)
Iteration	O(n)	Proportional to slice size
in check	O(n)	Worst case scans entire slice
Memory usage	O(1)	Constant overhead

Limitations

• Read-only (doesn't support item assignment)
• Underlying sequence must support integer indexing
• Slices must be within bounds of original sequence

Contributing

Contributions are welcome! Please submit pull requests or open issues on the GitHub repository.

License

This project is licensed under the MIT License.