capturegraph.data.containers

Vector Module - Vectorized Collection Types

This module provides types for vectorized operations on collections of objects, enabling NumPy-style broadcasting for attribute access and transforms.

Core Types

• List[T]: A list subclass that broadcasts attribute access across all elements. sessions.date returns a List of each session's date.

• Dict[V]: A dict subclass with attribute-style access (d.foo instead of d["foo"]). Keys must be strings.

• zip(**kwargs): Combines multiple Lists with NumPy-style broadcasting. Returns a List of Dicts for row-wise processing.

• MissingType: A null object for safe chaining. Absorbs all attribute access instead of raising AttributeError. Always carries a reason for debugging.

Example

import capturegraph.data as cg

sessions = cg.List([session1, session2, session3])

# Vectorized attribute access
ratings = sessions.tastiness_rating  # → List([5, 4, 3])

# Projection to dict subset
subset = sessions["date", "store"]  # → List of Dicts

# Apply function with .map()
names = sessions.date.map(lambda d: f"{d:%Y%m%d}.heic")

# Combine multiple Lists with zip
paths = cg.zip(dir=base, name=names).map(lambda r: r.dir / r.name)

# Safe chaining - returns MissingType instead of AttributeError
result = sessions.nonexistent.also_missing  # → MissingType(...)

Modules:

Name	Description
dict	Dict - Dictionary with Attribute Access
list	List - Vectorized Collection Operations
missing	MissingType - Null Object for Safe Chaining
utilities	Utilities for working with containers.