dispatch-on-structure

name	dispatch-on-structure
description	For heterogeneous data: pattern matching on type/structure, interpreter eval loops, handling different expression types.

dispatch-on-structure

When to Use

• Interpreters: different behavior per expression type
• Processing heterogeneous data
• Pattern matching (before Python 3.10 match)
• AST walkers
• Multi-type handlers

When NOT to Use

• Homogeneous data (use single code path)
• Object-oriented dispatch is clearer (use methods)
• Simple type checking suffices

The Pattern

Check structure/type of input and dispatch to appropriate handler.

def process(x):
    """Dispatch based on structure of x."""
    if isinstance(x, int):
        return handle_int(x)
    if isinstance(x, list) and len(x) == 0:
        return handle_empty()
    if isinstance(x, list) and x[0] == 'quote':
        return handle_quote(x[1])
    if isinstance(x, list):
        return handle_list(x)
    raise TypeError(f"Unknown type: {type(x)}")

Example (from pytudes lis.py)

def eval(x, env=global_env):
    """Evaluate an expression in an environment."""

    # Dispatch on structure of x
    if isinstance(x, Symbol):           # Variable reference
        return env[x]

    elif not isinstance(x, List):       # Constant literal
        return x

    elif x[0] == 'quote':               # (quote exp)
        (_, exp) = x
        return exp

    elif x[0] == 'if':                  # (if test conseq alt)
        (_, test, conseq, alt) = x
        exp = conseq if eval(test, env) else alt
        return eval(exp, env)

    elif x[0] == 'define':              # (define var exp)
        (_, var, exp) = x
        env[var] = eval(exp, env)

    elif x[0] == 'lambda':              # (lambda (var...) body)
        (_, parms, body) = x
        return Procedure(parms, body, env)

    else:                               # (proc arg...)
        proc = eval(x[0], env)
        args = [eval(exp, env) for exp in x[1:]]
         proc(*args)


 ():
    
     y == x:
         
      (y, Expression):
         
     (y.args) == :          
         D_unary(y, x)
     (y.args) == :          
         D_binary(y, x)
     ValueError()

Key Principles

1. Order matters: Check specific cases before general
2. Destructure inline: (_, test, conseq, alt) = x
3. isinstance for types: Check type before accessing
4. Sentinel values: Check x[0] == 'quote' for tagged lists
5. Fallback/error: Handle unknown cases explicitly