Interpreter Design Pattern
Video Lecture
Overview
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Terminology
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Interpreter UML Diagram
Source Code
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./interpreter/interpreter_concept.py
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77 | # pylint: disable=too-few-public-methods
"The Interpreter Pattern Concept"
class AbstractExpression():
"All Terminal and Non-Terminal expressions will implement an `interpret` method"
@staticmethod
def interpret():
"""
The `interpret` method gets called recursively for each
AbstractExpression
"""
class Number(AbstractExpression):
"Terminal Expression"
def __init__(self, value):
self.value = int(value)
def interpret(self):
return self.value
def __repr__(self):
return str(self.value)
class Add(AbstractExpression):
"Non-Terminal Expression."
def __init__(self, left, right):
self.left = left
self.right = right
def interpret(self):
return self.left.interpret() + self.right.interpret()
def __repr__(self):
return f"({self.left} Add {self.right})"
class Subtract(AbstractExpression):
"Non-Terminal Expression"
def __init__(self, left, right):
self.left = left
self.right = right
def interpret(self):
return self.left.interpret() - self.right.interpret()
def __repr__(self):
return f"({self.left} Subtract {self.right})"
# The Client
# The sentence complies with a simple grammar of
# Number -> Operator -> Number -> etc,
SENTENCE = "5 + 4 - 3 + 7 - 2"
print(SENTENCE)
# Split the sentence into individual expressions that will be added to
# an Abstract Syntax Tree (AST) as Terminal and Non-Terminal expressions
TOKENS = SENTENCE.split(" ")
print(TOKENS)
# Manually Creating an Abstract Syntax Tree from the tokens
AST: list[AbstractExpression] = [] # Python 3.9
# AST = [] # Python 3.8 or earlier
AST.append(Add(Number(TOKENS[0]), Number(TOKENS[2]))) # 5 + 4
AST.append(Subtract(AST[0], Number(TOKENS[4]))) # ^ - 3
AST.append(Add(AST[1], Number(TOKENS[6]))) # ^ + 7
AST.append(Subtract(AST[2], Number(TOKENS[8]))) # ^ - 2
# Use the final AST row as the root node.
AST_ROOT = AST.pop()
# Interpret recursively through the full AST starting from the root.
print(AST_ROOT.interpret())
# Print out a representation of the AST_ROOT
print(AST_ROOT)
|
Output
| python ./interpreter/interpreter_concept.py
5 + 4 - 3 + 7 - 2
['5', '+', '4', '-', '3', '+', '7', '-', '2']
11
((((5 Add 4) Subtract 3) Add 7) Subtract 2)
|
Example Use Case
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Example UML Diagram
Source Code
./interpreter/client.py
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20 | "The Interpreter Pattern Use Case Example"
from sentence_parser import Parser
# The sentence complies with a simple grammar of
# Number -> Operator -> Number -> etc,
SENTENCE = "5 + IV - 3 + VII - 2"
# SENTENCE = "V + IV - III + 7 - II"
# SENTENCE= "CIX + V"
# SENTENCE = "CIX + V - 3 + VII - 2"
# SENTENCE = "MMMCMXCIX - CXIX + MCXXII - MMMCDXII - XVIII - CCXXXV"
print(SENTENCE)
AST_ROOT = Parser.parse(SENTENCE)
# Interpret recursively through the full AST starting from the root.
print(AST_ROOT.interpret())
# Print out a representation of the AST_ROOT
print(AST_ROOT)
|
./interpreter/abstract_expression.py
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13 | "An Abstract Expression"
# pylint: disable=too-few-public-methods
class AbstractExpression():
"""
All Terminal and Non-Terminal expressions will implement an
`interpret` method
"""
@staticmethod
def interpret():
"""
The `interpret` method gets called recursively for
each AbstractExpression
"""
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./interpreter/number.py
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14 | "A Number. This is a leaf node Expression"
from abstract_expression import AbstractExpression
class Number(AbstractExpression):
"Terminal Expression"
def __init__(self, value):
self.value = int(value)
def interpret(self):
return self.value
def __repr__(self):
return str(self.value)
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./interpreter/add.py
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15 | "Add Expression. This is a Non-Terminal Expression"
from abstract_expression import AbstractExpression
class Add(AbstractExpression):
"Non-Terminal Expression."
def __init__(self, left, right):
self.left = left
self.right = right
def interpret(self):
return self.left.interpret() + self.right.interpret()
def __repr__(self):
return f"({self.left} Add {self.right})"
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./interpreter/subtract.py
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15 | "Subtract Expression. This is a Non-Terminal Expression"
from abstract_expression import AbstractExpression
class Subtract(AbstractExpression):
"Non-Terminal Expression"
def __init__(self, left, right):
self.left = left
self.right = right
def interpret(self):
return self.left.interpret() - self.right.interpret()
def __repr__(self):
return f"({self.left} Subtract {self.right})"
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./interpreter/roman_numeral.py
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77 | # pylint: disable=too-few-public-methods
"Roman Numeral Expression. This is a Non-Terminal Expression"
from abstract_expression import AbstractExpression
from number import Number
class RomanNumeral(AbstractExpression):
"Non Terminal expression"
def __init__(self, roman_numeral):
self.roman_numeral = roman_numeral
self.context = [roman_numeral, 0]
def interpret(self):
RomanNumeral1000.interpret(self.context)
RomanNumeral100.interpret(self.context)
RomanNumeral10.interpret(self.context)
RomanNumeral1.interpret(self.context)
return Number(self.context[1]).interpret()
def __repr__(self):
return f"{self.roman_numeral}({self.context[1]})"
class RomanNumeral1(RomanNumeral):
"Roman Numerals 1 - 9"
one = "I"
four = "IV"
five = "V"
nine = "IX"
multiplier = 1
@classmethod
def interpret(cls, *args):
context = args[0]
if not context[0]:
return Number(context[1]).interpret()
if context[0][0: 2] == cls.nine:
context[1] += (9 * cls.multiplier)
context[0] = context[0][2:]
elif context[0][0] == cls.five:
context[1] += (5 * cls.multiplier)
context[0] = context[0][1:]
elif context[0][0: 2] == cls.four:
context[1] += + (4 * cls.multiplier)
context[0] = context[0][2:]
while context[0] and context[0][0] == cls.one:
context[1] += (1 * cls.multiplier)
context[0] = context[0][1:]
return Number(context[1]).interpret()
class RomanNumeral10(RomanNumeral1):
"Roman Numerals 10 - 99"
one = "X"
four = "XL"
five = "L"
nine = "XC"
multiplier = 10
class RomanNumeral100(RomanNumeral1):
"Roman Numerals 100 - 999"
one = "C"
four = "CD"
five = "D"
nine = "CM"
multiplier = 100
class RomanNumeral1000(RomanNumeral1):
"Roman Numerals 1000 - 3999"
one = "M"
four = ""
five = ""
nine = ""
multiplier = 1000
|
./interpreter/sentence_parser.py
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69 | "A Custom Parser for creating an Abstract Syntax Tree"
from number import Number
from add import Add
from subtract import Subtract
from roman_numeral import RomanNumeral
class Parser:
"Dynamically create the Abstract Syntax Tree"
@classmethod
def parse(cls, sentence):
"Create the AST from the sentence"
tokens = sentence.split(" ")
print(tokens)
tree = [] # Abstract Syntax Tree
while len(tokens) > 1:
left_expression = cls.decide_left_expression(tree, tokens)
# get the operator, make the token list shorter
operator = tokens.pop(0)
right = tokens[0]
if not right.isdigit():
tree.append(RomanNumeral(tokens[0]))
if operator == '-':
tree.append(Subtract(left_expression, tree[-1]))
if operator == '+':
tree.append(Add(left_expression, tree[-1]))
else:
right_expression = Number(right)
if not tree:
# Empty Data Structures return False by default
if operator == '-':
tree.append(
Subtract(left_expression, right_expression))
if operator == '+':
tree.append(
Add(left_expression, right_expression))
else:
if operator == '-':
tree.append(Subtract(tree[-1], right_expression))
if operator == '+':
tree.append(Add(tree[-1], right_expression))
return tree.pop()
@staticmethod
def decide_left_expression(tree, tokens):
"""
On the First iteration, the left expression can be either a
number or roman numeral. Every consecutive expression is
reference to an existing AST row
"""
left = tokens.pop(0)
left_expression = None
if not tree: # only applicable if first round
if not left.isdigit(): # if 1st token a roman numeral
tree.append(RomanNumeral(left))
left_expression = tree[-1]
else:
left_expression = Number(left)
else:
left_expression = tree[-1]
return left_expression
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Output
| python ./interpreter/client.py
5 + IV - 3 + VII - 2
['5', '+', 'IV', '-', '3', '+', 'VII', '-', '2']
11
((((5 Add IV(4)) Subtract 3) Add VII(7)) Subtract 2)
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New Coding Concepts
String Slicing
Sometimes you want part of a string. In the example code, when I am interpreting the roman numerals, I am comparing the first one or two characters in the context with IV or CM or many other roman numeral combinations. If the match is true then I continue with further commands.
The format is
E.g., the string may be
and I want the first three characters,
| test = "MMMCMXCIX"
print(test[0: 3])
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Outputs
or I want the last 4 characters
| test = "MMMCMXCIX"
print(test[-4:])
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Outputs
or I want a section in the middle
| test = "MMMCMXCIX"
print(test[2:5])
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Outputs
or stepped
| test = "MMMCMXCIX"
print(test[2:9:2])
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Outputs
or even reversed
| test = "MMMCMXCIX"
print(test[::-1])
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Outputs
The technique is very common in examples of Python source code throughout the internet. So, when you see the [] with numbers and colons inside, eg, [:-1:] , it is likely to do with extracting a portion of a data structure.
Note that the technique also works on Lists and Tuples.
| test = [1,2,3,4,5,6,7,8,9]
print(test[0: 3])
print(test[-4:])
print(test[2:5])
print(test[2:9:2])
print(test[::-1])
print(test[:-1:])
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Outputs
| [1, 2, 3]
[6, 7, 8, 9]
[3, 4, 5]
[3, 5, 7, 9]
[9, 8, 7, 6, 5, 4, 3, 2, 1]
[1, 2, 3, 4, 5, 6, 7, 8]
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Dunder __repr__ Method
It is used in a very similar way to the __str__ dunder method. You can override it to produce a string representation of a class.
| class class_a():
def __repr__(self):
return "I am __repr__"
A = class_a()
print(A)
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Outputs
If you have a class that also overrides the __str__ dunder method already, then printing it will default to use the __str__ override instead.
| class class_a():
def __str__(self):
return "I am __str__"
def __repr__(self):
return "I am __repr__"
A = class_a()
print(A)
|
Outputs
You should prefer to use the __str__ method to print human readable versions of your classes instead. If you require something with more information that could alternatively be used for debugging, or for object recreation using eval() , and not intended for reading by users, then it is generally recommended to implement the __repr__ method instead of __str__ for these more programmatic purposes.
To specifically use a __repr__ output, where both __repr__ and __str__ are both implemented in the same class, then use object.__repr__() or repr(A),
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12 | class class_a():
def __str__(self):
return "I am __str__"
def __repr__(self):
return "I am __repr__"
A = class_a()
print(A.__repr__())
#or
print(repr(A))
|
Summary
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