apply-interpreter-pattern

name	apply-interpreter-pattern
description	Use when you need to interpret sentences in a simple language — defining a grammar as a class hierarchy where each rule is a class and interpreting an expression is traversing that hierarchy.
source	Gamma, Helm, Johnson, Vlissides, "Design Patterns: Elements of Reusable Object-Oriented Software" (1994) pp. 243–255; Python ast module; SQL query parsers; regular expression engines; Excel formula evaluation
tags	["design-patterns","behavioral","interpreter","oop","developer","language-processing","expression-evaluation"]
related	["apply-composite-pattern","apply-visitor-pattern","apply-solid-principles"]

Apply Interpreter Pattern

Define a grammar for a language and represent each grammar rule as a class, using composition to interpret expressions.

Why This Is Best Practice

Adopted by: Python's ast module (every Python expression is an AST node that interprets itself — the foundation of all Python compilers, linters, and tools), Java's javax.script (script interpreter architecture), SQL database engines (query expressions are parsed into an AST where each node knows how to evaluate itself), and Excel (cell formula evaluation traverses an expression tree). Impact: GoF documents that Interpreter makes grammar rules independently changeable and combinable. Python's ast module design enables the entire ecosystem of static analysis tools (Flake8, mypy, Bandit) — each tool visits the same expression tree without modifying the parser. Why best: The alternative — a large if/elif parser — puts all rules in one method. Adding a new grammar rule requires modifying that method. Interpreter makes each rule an independent class — adding a rule means adding a class, not editing existing code.

Sources: Gamma et al. (1994) pp. 243–255; Python ast module documentation; ANTLR4 documentation (widely-used parser generator that embodies the Interpreter pattern)

Steps

Step 1: Define the grammar (small and simple — this pattern suits narrow DSLs)

<expression> ::= <number>
               | <expression> '+' <expression>
               | <expression> '*' <expression>

Step 2: Define the abstract expression interface

from abc import ABC, abstractmethod

class Expression(ABC):
    @abstractmethod
    def interpret(self, context: dict) -> int: ...

Step 3: Implement terminal expressions (leaves — no sub-expressions)

class NumberExpression(Expression):
    def __init__(self, value: int):
        self._value = value

    def interpret(self, context: dict) -> int:
        return self._value

class VariableExpression(Expression):
    def __init__(self, name: str):
        self._name = name

    def interpret(self, context: dict) -> int:
        return context[self._name]

Step 4: Implement non-terminal expressions (composites — have sub-expressions)

class AddExpression(Expression):
    def __init__(self, left: Expression, right: Expression):
        self._left = left
        self._right = right

    def interpret(self, context: dict) -> int:
        return self._left.interpret(context) + self._right.interpret(context)

class MultiplyExpression(Expression):
    def __init__(self, left: Expression, right: Expression):
        self._left = left
        self._right = right

    def interpret(self, context: dict) -> int:
        return self._left.interpret(context) * self._right.interpret(context)

Step 5: Build and interpret an expression tree

# Represents: (x + 3) * 2
context = {"x": 5}

expr = MultiplyExpression(
    AddExpression(VariableExpression("x"), NumberExpression(3)),
    NumberExpression(2)
)

print(expr.interpret(context))   # (5 + 3) * 2 = 16

Note: expression trees are typically built by a parser, not manually. Interpreter defines the evaluation step; parsing is a separate concern.

When NOT to Use

• Complex grammars — GoF explicitly warns against using Interpreter for complex languages. Use a real parser generator (ANTLR, PLY, lark-parser) instead.
• Performance-critical expression evaluation — recursive tree traversal is slow for large expressions. Compiled languages parse to bytecode for a reason.
• When an existing library covers the domain — regular expressions (re), SQL (sqlparse), and math expressions (sympy) have mature parsers. Don't reimplement them.

Common Mistakes

Using Interpreter for a complex language. If the grammar has more than 10 rules or requires backtracking, use a parser generator. Interpreter doesn't scale to real languages.

Mixing parsing and interpretation. The Interpreter pattern covers evaluation of an already-parsed expression tree. Building the tree (parsing) is a separate step and should be separate code.

Not handling context errors. If context["x"] is missing, VariableExpression.interpret() raises KeyError. Validate context before interpretation or catch and wrap errors.