Cooking Python in Emacs

OpenAI Assistance with Python code interpreter

Preamble

The purpose of this article is to test the dexterity of the OpenAI Assistant in solving programming tasks based on their descriptions in English and the associated test suite requirements.

Prerequisites

OpenAI Assistant with code_interpreter as the tool and instructions:

You are an experienced Python programmer proficient in test-driven development.

Functional Programming

A primitive task

Description

Write a function get_vowels_count that returns the number (count) of vowels in the given string. We will consider a, e, i, o, and u as vowels.

get_vowels_count must pass this assertion: 

assert (get_vowels_count('John the dully boy write this book') == 9)

Answer

  def get_vowels_count(s):
      return sum(1 for char in s.lower() if char in 'aeiou')

  # Assertion to validate the function
  assert (get_vowels_count('John the dully boy write this book') == 9)

A solution requiring nuanced comprehension

Task description

Write a function last_digit that takes in two numbers a and b and returns the last decimal digit of a^b. Note that a and b may be very large!

For example, the last decimal digit of 97 is 9, since 97 = 4782969. The last decimal digit of (2200)(2300), which has over 1092 decimal digits, is 6.

The inputs to your function will always be non-negative integers.

last_digit must pass successfully through all of these assertions: 

assert(last_digit(4, 1) == 4)
assert(last_digit(4, 2) == 6)
assert(last_digit(9, 7) == 9)
assert(last_digit(10, 10 ** 10) == 0)
assert(last_digit(2 ** 200, 2 ** 300) == 6)

Answer

  def last_digit(a, b):
      if b == 0:
          return 1
      return pow(a, b, 10)

  # Assertions to validate the function
  assert(last_digit(4, 1) == 4)
  assert(last_digit(4, 2) == 6)
  assert(last_digit(9, 7) == 9)
  assert(last_digit(10, 10 ** 10) == 0)
  assert(last_digit(2 ** 200, 2 ** 300) == 6)

Validation

# Just a test
  print(pow(2**200, 2**300, 10))

6

Conclusion

Not bad at all!!!

Tony

Raw and obscure description

Test the ability to infer by submitting a poorly formatted task.

Description

Consider a sequence u where u is defined as follows:

The number u(0) = 1 is the first one in u. For each x in u, then y = 2 * x + 1 and z = 3 * x + 1 must be in u too. There are no other numbers in u. Ex: u = [1, 3, 4, 7, 9, 10, 13, 15, 19, 21, 22, 27, …]

1 gives 3 and 4, then 3 gives 7 and 10, 4 gives 9 and 13, then 7 gives 15 and 22 and so on…

Task:

Given parameter n the function dbl_linear (or dblLinear…) returns the element u(n) of the ordered (with <) sequence u.

Example:

dbl_linear(10) should return 22

Note:

Focus attention on efficiency

Answer

  from heapq import heappop, heappush

  def dbl_linear(n):
      u = [1]
      seen = {1}
    
      for _ in range(n):
          x = heappop(u)
          for y in [2 * x + 1, 3 * x + 1]:
              if y not in seen:
                  seen.add(y)
                  heappush(u, y)
                
      return heappop(u)

  # Example assertion to validate the function
  assert(dbl_linear(10) == 22)

A more complex task

Description

For a given chemical formula represented by a string, count the number of atoms of each element contained in the molecule and return an object.

For example:

water = 'H2O' parse_molecule(water) # return {H: 2, O: 1}

magnesium_hydroxide = 'Mg(OH)2' parse_molecule(magnesium_hydroxide) # return {Mg: 1, O: 2, H: 2}

var fremy_salt = 'K4[ON(SO3)2]2' parse_molecule(fremySalt) # return {K: 4, O: 14, N: 2, S: 4}

As you can see, some formulas have brackets in them. The index outside the brackets tells you that you have to multiply count of each atom inside the bracket on this index. For example, in Fe(NO3)2 you have one iron atom, two nitrogen atoms and six oxygen atoms.

Note that brackets may be round, square or curly and can also be nested. Index after the braces is optional.

Answer

import re
from collections import defaultdict

def parse_molecule(formula):
    def multiply_dict(d, n):
        return {k: v * n for k, v in d.items()}

    def parse_section(section):
        atoms = defaultdict(int)
        i = 0
        while i < len(section):
            if section[i].isalpha():
                j = i + 1
                while j < len(section) and section[j].islower():
                    j += 1
                element = section[i:j]
                k = j
                while k < len(section) and section[k].isdigit():
                    k += 1
                count = int(section[j:k] or 1)
                atoms[element] += count
                i = k
            elif section[i] in '([{':
                stack = []
                brackets = {'(': ')', '[': ']', '{': '}'}
                close_bracket = brackets[section[i]]
                for j in range(i, len(section)):
                    if section[j] == section[i]:
                        stack.append(section[i])
                    elif section[j] == close_bracket:
                        stack.pop()
                    if not stack:
                        break
                content = parse_section(section[i + 1: j])
                k = j + 1
                while k < len(section) and section[k].isdigit():
                    k += 1
                multiplier = int(section[j + 1: k] or 1)
                content = multiply_dict(content, multiplier)
                for key, val in content.items():
                    atoms[key] += val
                i = k
        return atoms

    return parse_section(formula)

# Example assertions to validate the function
if (parse_molecule('H2O') == {'H': 2, 'O': 1}):
    print("Water!")

assert parse_molecule('Mg(OH)2') == {'Mg': 1, 'O': 2, 'H': 2}
assert parse_molecule('K4[ON(SO3)2]2') == {'K': 4, 'O': 14, 'N': 2, 'S': 4}

Water!

Sum up

The assistant even wrote a set of assertions to prove the correctness of his code.

Awesome!

Another check of Assistant's dexterity

Task description

You have to create a function that takes a positive integer number and returns the next bigger number formed by the same digits:

next_bigger(12)==21 next_bigger(513)==531 next_bigger(2017)==2071

If no bigger number can be composed using those digits, return -1:

next_bigger(9)==-1 next_bigger(111)==-1 next_bigger(531)==-1

Answer

def next_bigger(n):
    digits = list(str(n))
  
    # Find the rightmost digit that is smaller than the digit next to it
    for i in range(len(digits) - 2, -1, -1):
        if digits[i] < digits[i + 1]:
            break
    else:
        return -1
  
    # Find the smallest digit on the right that is larger than digits[i]
    for j in range(len(digits) - 1, i, -1):
        if digits[j] > digits[i]:
            break
  
    # Swap the two digits
    digits[i], digits[j] = digits[j], digits[i]
  
    # Reverse the digits to the right of i
    digits = digits[:i + 1] + sorted(digits[i + 1:])
  
    return int(''.join(digits))

# Example assertions to validate the function
assert next_bigger(12) == 21
assert next_bigger(513) == 531
assert next_bigger(2017) == 2071
assert next_bigger(9) == -1
assert next_bigger(111) == -1
assert next_bigger(531) == -1
# my own test to be sure:
if next_bigger(123456789) == 123456798:
    print("Whoa!")

Whoa!

Thread-specific question

To test the aptitude to make contextual (conversation Thread related) suggestions.

Task

Write the function parse_molecule without using the standard library modules re and collections.

Solution

def parse_molecule(formula):
    def multiply_dict(d, n):
        for k in d:
            d[k] *= n
        return d
  
    def parse_section(section):
        atoms = {}
        stack = []
        multipliers = [1]
        n = len(section)
        i = 0
      
        while i < n:
            if section[i].isalpha():
                start = i
                i += 1
                while i < n and section[i].islower():
                    i += 1
                element = section[start:i]
                start = i
                while i < n and section[i].isdigit():
                    i += 1
                count = int(section[start:i]) if start != i else 1
                atoms[element] = atoms.get(element, 0) + count * multipliers[-1]
            elif section[i] in '([{':
                stack.append(atoms)
                atoms = {}
                multipliers.append(multipliers[-1])
                i += 1
            elif section[i] in ')]}':
                i += 1
                start = i
                while i < n and section[i].isdigit():
                    i += 1
                multiplier = int(section[start:i]) if start != i else 1
                atoms = multiply_dict(atoms, multiplier)
                if stack:
                    prev_atoms = stack.pop()
                    for k, v in atoms.items():
                        prev_atoms[k] = prev_atoms.get(k, 0) + v
                    atoms = prev_atoms
                multipliers.pop()
            else:
                i += 1

        return atoms
  
    return parse_section(formula)

# Example assertions to validate the function
assert parse_molecule('H2O') == {'H': 2, 'O': 1}
assert parse_molecule('Mg(OH)2') == {'Mg': 1, 'O': 2, 'H': 2}
assert parse_molecule('K4[ON(SO3)2]2') == {'K': 4, 'O': 14, 'N': 2, 'S': 4}
# my own check-up:
if parse_molecule('H2O2') == {'H': 2, 'O': 2}:
    print("It is a hydrogen peroxide")

It is a hydrogen peroxide

The Snag

The balance between task intricacy and ambiguity of description.

Question

Optimize the function parse_molecule: 

import re
from collections import defaultdict

def parse_molecule(formula):
    def multiply_dict(d, n):
        return {k: v * n for k, v in d.items()}
  
    def parse_section(section):
        atoms = defaultdict(int)
        i = 0
        while i < len(section):
            if section[i].isalpha():
                j = i + 1
                while j < len(section) and section[j].islower():
                    j += 1
                element = section[i:j]
                k = j
                while k < len(section) and section[k].isdigit():
                    k += 1
                count = int(section[j:k] or 1)
                atoms[element] += count
                i = k
            elif section[i] in '([{':
                stack = []
                brackets = {'(': ')', '[': ']', '{': '}'}
                close_bracket = brackets[section[i]]
                for j in range(i, len(section)):
                    if section[j] == section[i]:
                        stack.append(section[i])
                    elif section[j] == close_bracket:
                        stack.pop()
                    if not stack:
                        break
                content = parse_section(section[i + 1: j])
                k = j + 1
                while k < len(section) and section[k].isdigit():
                    k += 1
                multiplier = int(section[j + 1: k] or 1)
                content = multiply_dict(content, multiplier)
                for key, val in content.items():
                    atoms[key] += val
                i = k
        return atoms
      
    return parse_section(formula)

it must successfully pass through this set of assertions: 

assert parse_molecule('H2O') == {'H': 2, 'O': 1}
assert parse_molecule('Mg(OH)2') == {'Mg': 1, 'O': 2, 'H': 2}
assert parse_molecule('K4[ON(SO3)2]2') == {'K': 4, 'O': 14, 'N': 2, 'S': 4}

Answer

def parse_molecule(formula):
    def multiply_dict(d, n):
        for k in d:
            d[k] *= n
        return d
    
    def parse_section(section, multiplier=1):
        atoms = {}
        stack = []
        multipliers = [multiplier]
        n = len(section)
        i = 0
        
        while i < n:
            if section[i].isalpha():
                start = i
                i += 1
                while i < n and section[i].islower():
                    i += 1
                element = section[start:i]
                start = i
                while i < n and section[i].isdigit():
                    i += 1
                count = int(section[start:i]) if start != i else 1
                atoms[element] = atoms.get(element, 0) + count * multipliers[-1]
            elif section[i] in '([{':
                stack.append((atoms, multipliers.pop()))
                atoms, multipliers[-1] = {}, 1
                multipliers.append(multiplier)
                i += 1
            elif section[i] in ')]}':
                i += 1
                start = i
                while i < n and section[i].isdigit():
                    i += 1
                sub_multiplier = int(section[start:i]) if start != i else 1
                if stack:
                    atoms = multiply_dict(atoms, sub_multiplier)
                    prev_atoms, prev_multiplier = stack.pop()
                    for k, v in atoms.items():
                        prev_atoms[k] = prev_atoms.get(k, 0) + v * prev_multiplier
                    atoms = prev_atoms
                multipliers.pop()
            else:
                i += 1

        return atoms
    
    return parse_section(formula)

# Example assertions to validate the function
assert parse_molecule('H2O') == {'H': 2, 'O': 1}
assert parse_molecule('Mg(OH)2') == {'Mg': 1, 'O': 2, 'H': 2}
assert parse_molecule('K4[ON(SO3)2]2') == {'K': 4, 'O': 14, 'N': 2, 'S': 4}

It is the limit!

Object-Oriented Programming

Double Linked List

Write the OOP implementation of double-linked list, and the test suite to check up its main features:

  • add node;
  • delete node;
  • etc.

Implementation

Here's the implementation of a double-linked list in Python with a basic test suite to verify its main functionalities. 

class Node:
    def __init__(self, value):
        self.value = value
        self.next = None
        self.prev = None

class DoubleLinkedList:
    def __init__(self):
        self.head = None
        self.tail = None
        
    def add_node(self, value):
        new_node = Node(value)
        if not self.head:
            self.head = self.tail = new_node
        else:
            self.tail.next = new_node
            new_node.prev = self.tail
            self.tail = new_node
            
    def delete_node(self, value):
        current = self.head
        while current:
            if current.value == value:
                if current.prev:
                    current.prev.next = current.next
                else:
                    self.head = current.next
                if current.next:
                    current.next.prev = current.prev
                else:
                    self.tail = current.prev
                return True
            current = current.next
        return False
    
    def find_node(self, value):
        current = self.head
        while current:
            if current.value == value:
                return current
            current = current.next
        return None
    
    def to_list(self):
        result = []
        current = self.head
        while current:
            result.append(current.value)
            current = current.next
        return result

def test_double_linked_list():
    dll = DoubleLinkedList()
    # Test add_node
    dll.add_node(1)
    dll.add_node(2)
    dll.add_node(3)
    assert dll.to_list() == [1, 2, 3], f"Expected: [1, 2, 3], Got: {dll.to_list()}"

    # Test find_node
    node = dll.find_node(2)
    assert node is not None and node.value == 2, f"Expected: 2, Got: {node.value if node else None}"
    
    node = dll.find_node(4)
    assert node is None, f"Expected: None, Got: {node.value if node else None}"
    
    # Test delete_node
    assert dll.delete_node(2) == True, "Node with value 2 should be found and deleted"
    assert dll.to_list() == [1, 3], f"Expected: [1, 3], Got: {dll.to_list()}"
    
    assert dll.delete_node(2) == False, "Node with value 2 should not be found"
    
    assert dll.delete_node(1) == True, "Node with value 1 should be found and deleted"
    assert dll.to_list() == [3], f"Expected: [3], Got: {dll.to_list()}"
    
    assert dll.delete_node(3) == True, "Node with value 3 should be found and deleted"
    assert dll.to_list() == [], f"Expected: [], Got: {dll.to_list()}"
    
    assert dll.delete_node(3) == False, "Node with value 3 should not be found"
    print("All tests are passed successfully")

Run tests

test_double_linked_list()

All tests are passed successfully

You can run the test_doubly_linked_list function to verify that the doubly-linked list implementation works as expected. This test suite checks the main features such as adding nodes, deleting nodes, finding nodes, and converting the list to a Python list.

Modification

Task

Modify class DoubleLinkedList by converting method to_list into __repr__ and the test suite accordingly with this modification.

Resolution

Here's the modified implementation of the DoublyLinkedList class, where the to_list method has been converted into the __repr__ method. The test suite has also been updated accordingly. 

class Node:
    def __init__(self, value):
        self.value = value
        self.next = None
        self.prev = None

class DoubleLinkedList:
    def __init__(self):
        self.head = None
        self.tail = None
        
    def add_node(self, value):
        new_node = Node(value)
        if not self.head:
            self.head = self.tail = new_node
        else:
            self.tail.next = new_node
            new_node.prev = self.tail
            self.tail = new_node
            
    def delete_node(self, value):
        current = self.head
        while current:
            if current.value == value:
                if current.prev:
                    current.prev.next = current.next
                else:
                    self.head = current.next
                if current.next:
                    current.next.prev = current.prev
                else:
                    self.tail = current.prev
                return True
            current = current.next
        return False
    
    def find_node(self, value):
        current = self.head
        while current:
            if current.value == value:
                return current
            current = current.next
        return None

    def __repr__(self):
        result = []
        current = self.head
        while current:
            result.append(current.value)
            current = current.next
        return str(result)


# Modified Test Suite for Double-Linked List

def test_double_linked_list():
    dll = DoubleLinkedList()
    
    # Test add_node
    dll.add_node(1)
    dll.add_node(2)
    dll.add_node(3)
    assert repr(dll) == str([1, 2, 3]), f"Expected: [1, 2, 3], Got: {repr(dll)}"
    
    # Test find_node
    node = dll.find_node(2)
    assert node is not None and node.value == 2, f"Expected: 2, Got: {node.value if node else None}"
    
    node = dll.find_node(4)
    assert node is None, f"Expected: None, Got: {node.value if node else None}"
    
    # Test delete_node
    assert dll.delete_node(2) == True, "Node with value 2 should be found and deleted"
    assert repr(dll) == str([1, 3]), f"Expected: [1, 3], Got: {repr(dll)}"
    
    assert dll.delete_node(2) == False, "Node with value 2 should not be found"
    
    assert dll.delete_node(1) == True, "Node with value 1 should be found and deleted"
    assert repr(dll) == str([3]), f"Expected: [3], Got: {repr(dll)}"
    
    assert dll.delete_node(3) == True, "Node with value 3 should be found and deleted"
    assert repr(dll) == str([]), f"Expected: [], Got: {repr(dll)}"
    
    assert dll.delete_node(3) == False, "Node with value 3 should not be found"

# Run tests
test_double_linked_list()
print("All tests passed!")

All tests passed!

You can run the test_double_linked_list function to verify that the double-linked list implementation works as expected. This test suite checks the main features such as adding nodes, deleting nodes, finding nodes, and uses the __repr__ method to convert the list to a string representation for comparison.

Extension

Task

The name of class is not DoublyLinkedList but DoubleLinkedList, bear it in your mind, please.

Add the feature to prevent same nodes inclusion into the DoubleLinkedList. Each node must have the unique value. The attempt to insert the node with not unique value must throw the Exception: "This value is already in the list!"

Answer

Here's the updated implementation of the DoubleLinkedList class with the feature to ensure unique node values. If an attempt is made to insert a node with a non-unique value, an Exception is raised with the message "This value is already in the list!". 

class Node:
    def __init__(self, value):
        self.value = value
        self.next = None
        self.prev = None

class DoubleLinkedList:
    def __init__(self):
        self.head = None
        self.tail = None
        self.values = set()
        
    def add_node(self, value):
        if value in self.values:
            raise Exception("This value is already in the list!")
        
        new_node = Node(value)
        if not self.head:
            self.head = self.tail = new_node
        else:
            self.tail.next = new_node
            new_node.prev = self.tail
            self.tail = new_node
        self.values.add(value)
            
    def delete_node(self, value):
        current = self.head
        while current:
            if current.value == value:
                self.values.remove(value)
                if current.prev:
                    current.prev.next = current.next
                else:
                    self.head = current.next
                if current.next:
                    current.next.prev = current.prev
                else:
                    self.tail = current.prev
                return True
            current = current.next
        return False
    
    def find_node(self, value):
        current = self.head
        while current:
            if current.value == value:
                return current
            current = current.next
        return None

    def __repr__(self):
        result = []
        current = self.head
        while current:
            result.append(current.value)
            current = current.next
        return str(result)


# >> Updated Test Suite for Double-Linked List

def test_double_linked_list():
    dll = DoubleLinkedList()
    
    # Test add_node
    dll.add_node(1)
    dll.add_node(2)
    dll.add_node(3)
    assert repr(dll) == str([1, 2, 3]), f"Expected: [1, 2, 3], Got: {repr(dll)}"
    
    # Test add_node with duplicate value
    try:
        dll.add_node(2)
        assert False, "Expected an exception for duplicate value"
    except Exception as e:
        assert str(e) == "This value is already in the list!", f"Expected: 'This value is already in the list!', Got: {str(e)}"
    
    # Test find_node
    node = dll.find_node(2)
    assert node is not None and node.value == 2, f"Expected: 2, Got: {node.value if node else None}"
    
    node = dll.find_node(4)
    assert node is None, f"Expected: None, Got: {node.value if node else None}"
    
    # Test delete_node
    assert dll.delete_node(2) == True, "Node with value 2 should be found and deleted"
    assert repr(dll) == str([1, 3]), f"Expected: [1, 3], Got: {repr(dll)}"
    
    assert dll.delete_node(2) == False, "Node with value 2 should not be found"
    
    assert dll.delete_node(1) == True, "Node with value 1 should be found and deleted"
    assert repr(dll) == str([3]), f"Expected: [3], Got: {repr(dll)}"
    
    assert dll.delete_node(3) == True, "Node with value 3 should be found and deleted"
    assert repr(dll) == str([]), f"Expected: [], Got: {repr(dll)}"
    
    assert dll.delete_node(3) == False, "Node with value 3 should not be found"

# Run tests
test_double_linked_list()
print("All tests passed!")

All tests passed!

You can run the test_double_linked_list function to verify that the DoubleLinkedList class works as expected. The test suite checks that duplicate values are not allowed and that the main functionalities such as adding nodes, deleting nodes, and finding nodes work correctly.

Customization

Question

Rewrite test_double_linked_list in unittest style, please.

Answer

Here's the modified test suite for the DoubleLinkedList class using the unittest framework. 

import unittest

class TestDoubleLinkedList(unittest.TestCase):
    def setUp(self):
        self.dll = DoubleLinkedList()
        
    def test_add_node(self):
        self.dll.add_node(1)
        self.dll.add_node(2)
        self.dll.add_node(3)
        self.assertEqual(repr(self.dll), str([1, 2, 3]))
        
    def test_add_duplicate_node(self):
        self.dll.add_node(1)
        self.dll.add_node(2)
        with self.assertRaises(Exception) as context:
            self.dll.add_node(2)
        self.assertEqual(str(context.exception), "This value is already in the list!")
    
    def test_find_node(self):
        self.dll.add_node(1)
        self.dll.add_node(2)
        self.dll.add_node(3)
        node = self.dll.find_node(2)
        self.assertIsNotNone(node)
        self.assertEqual(node.value, 2)
        
        node = self.dll.find_node(4)
        self.assertIsNone(node)
    
    def test_delete_node(self):
        self.dll.add_node(1)
        self.dll.add_node(2)
        self.dll.add_node(3)
        
        self.assertTrue(self.dll.delete_node(2))
        self.assertEqual(repr(self.dll), str([1, 3]))
        
        self.assertFalse(self.dll.delete_node(2))
        
        self.assertTrue(self.dll.delete_node(1))
        self.assertEqual(repr(self.dll), str([3]))
        
        self.assertTrue(self.dll.delete_node(3))
        self.assertEqual(repr(self.dll), str([]))
        
        self.assertFalse(self.dll.delete_node(3))
unittest.main(exit=False) # Emacs' Babel unittest run approach

....
----------------------------------------------------------------------
Ran 4 tests in 0.000s

OK

This unittest test suite includes the following tests:

  1. test_add_node: Tests adding nodes to the list.
  2. test_add_duplicate_node: Tests that adding a duplicate node raises an exception.
  3. test_find_node: Tests finding existing and non-existing nodes in the list.
  4. test_delete_node: Tests deleting nodes from the list.

To run the tests, save the code in a file and execute the file. The unittest framework will discover and run all the test methods.

Clarification

Question

Rewrite class TestDoubleLinkedList:

The chunks like 

        self.dll.add_node(1)
        self.dll.add_node(2)
        self.dll.add_node(3)

are redundant and unnecessary repetition. Put them into setUp method.

Answer

Sure, here's the updated test suite for the DoubleLinkedList, where the repetitive setup code has been moved into the setUp method. 

import unittest

class DoubleLinkedList:
    def __init__(self):
        self.head = None
        self.tail = None
        self.values = set()

    def add_node(self, value):
        if value in self.values:
            raise Exception("This value is already in the list!")

        new_node = Node(value)
        if not self.head:
            self.head = self.tail = new_node
        else:
            self.tail.next = new_node
            new_node.prev = self.tail
            self.tail = new_node
        self.values.add(value)

    def delete_node(self, value):
        current = self.head
        while current:
            if current.value == value:
                self.values.remove(value)
                if current.prev:
                    current.prev.next = current.next
                else:
                    self.head = current.next
                if current.next:
                    current.next.prev = current.prev
                else:
                    self.tail = current.prev
                return True
            current = current.next
        return False

    def find_node(self, value):
        current = self.head
        while current:
            if current.value == value:
                return current
            current = current.next
        return None

    def __repr__(self):
        result = []
        current = self.head
        while current:
            result.append(current.value)
            current = current.next
        return str(result)


class Node:
    def __init__(self, value):
        self.value = value
        self.next = None
        self.prev = None


class TestDoubleLinkedList(unittest.TestCase):
    def setUp(self):
        self.dll = DoubleLinkedList()
        self.dll.add_node(1)
        self.dll.add_node(2)
        self.dll.add_node(3)
        
    def test_add_node(self):
        self.assertEqual(repr(self.dll), str([1, 2, 3]))
        
    def test_add_duplicate_node(self):
        with self.assertRaises(Exception) as context:
            self.dll.add_node(2)
        self.assertEqual(str(context.exception), "This value is already in the list!")
    
    def test_find_node(self):
        node = self.dll.find_node(2)
        self.assertIsNotNone(node)
        self.assertEqual(node.value, 2)
        
        node = self.dll.find_node(4)
        self.assertIsNone(node)
    
    def test_delete_node(self):
        self.assertTrue(self.dll.delete_node(2))
        self.assertEqual(repr(self.dll), str([1, 3]))
        
        self.assertFalse(self.dll.delete_node(2))
        
        self.assertTrue(self.dll.delete_node(1))
        self.assertEqual(repr(self.dll), str([3]))
        
        self.assertTrue(self.dll.delete_node(3))
        self.assertEqual(repr(self.dll), str([]))
        
        self.assertFalse(self.dll.delete_node(3))
unittest.main(exit=False)

....
----------------------------------------------------------------------
Ran 4 tests in 0.000s

OK
  • The setUp method now initializes the list and adds the nodes 1, 2, and 3 for each test method.
  • Each test now assumes the list has these three elements from the start, reducing redundancy and unnecessary repetition.
  • The DoubleLinkedList and Node classes are now included in the same file for completeness.

Corollary

Question

What is your opinion about writing Python code using the OpenAI Assistant equipped with the code interpreter tool? I see it as a killer feature, beyond a doubt. What are your thoughts on including test suites for the generated code? Is it necessary to provide the test suites beforehand to simplify and clarify the task of Python code generation?

Answer

  Using an AI assistant equipped with a code interpreter tool is indeed
  a powerful feature that can greatly enhance productivity and code
  quality by providing quick feedback and validation of the generated
  code. Including test suites for the generated code is not only
  beneficial but practically necessary for ensuring the correctness and
  robustness of the implementations. Providing the test suites
  beforehand can indeed simplify and clarify the task of Python code
  generation, as it sets clear expectations and constraints, enabling
  more focused and accurate responses.

An Acid Note

Despite the powerful OpenAI algorithms, the cornerstone of success in augmented Python development is prompt clarity. A vague, uncertain, and convoluted task description results in incorrect answers.

The human factors remain the weakest link in the code development chain.