def main():
    # Cargamos pass

    a = load_env_tx_sign_pass('wif_posting_key')

    #h = Hive(node="https://api.hive.blog")
    q = Query()
    d = Discussions()

    # Nombre de usuario a verificar
    usuario_a_verificar = "subidu"

    # Definir expresión regular para encontrar etiquetas HTML
    html_tags_regex = re.compile(r"<[^>]+>")

    # Obtener la lista de publicaciones -> List[Class: Comment]
    posts_generator = d.get_discussions("created", q, limit=2000)

    # Contador de post publicados
    count_post_publicados = 0
    count_post_modificados = 0

    X = 0

    # Cargo la lista de autores con respuestas preconfiguradas
    autores_preconfig = author_preconfig()

    # Iterar sobre el generador
    for post in posts_generator:
        if post["author"] == "USERNAME_1":
            continue
        if X % 50 == 0:
            print(f"post.items.created: {post['created']}")
        X += 1
        print(X)
        """# Si el autor esta en la lista de baneados salta a la siguiente iteracion
        if author_in_banned_list(post["author"]):
            continue"""

        # Crear un objeto Comment para el post
        post_comment = Comment(
            #authorperm="cryptochroma/woo-token-giveaway-woo-4-ffc"#, blockchain_instance=h
            authorperm=f"{post['author']}/{post['permlink']}"#, blockchain_instance=h
        )

        replies = post_comment.get_replies()

        # Contar respuestas filtradas que contienen la palabra "count"
        count_replies = [
            reply for reply in replies if "count me " in reply["body"].lower()
        ]
        print("Numero de respuestas del post 'count me': ",len(count_replies))
        # Verificar si al menos cuatro usuarios han comentado "count"
        unique_users = set(reply["author"] for reply in count_replies)
        if len(unique_users) < 3:
            continue

        # Verificar si el usuario ha respondido
        usuario_respondio = False
        for ax in replies:
            if ax["author"].lower() == usuario_a_verificar:
                comentario_publicado = ax["body"]
                permlink_publicado = ax["permlink"]
                usuario_respondio = True
                break

        # preparamos comentario
        comment_author = "subidu"
        comment_parent_author = post["author"]
        comment_parent_permlink = post["permlink"]
        comment_title = ""
        comment_body = "Count me in ^^ @subidu"

        # Bloque: buscar palabras que mas se repitan
        replies_all_data = post_comment.get_replies(raw_data=True)
        # Filtrar respuestas que contienen etiquetas HTML
        filtered_replies = [
            reply["body"].lower()
            for reply in replies_all_data
            if not re.search(html_tags_regex, reply["body"])
        ]

        # Lista de respuesta filtrada sin etiquetas html
        list_replies_filtered = set(filtered_replies)

        all_sentences = [
            sentence
            for content in list_replies_filtered
            for sentence in extract_sentences(content)
        ]
        if len(all_sentences) > 1:
            #print("lista completa:",all_sentences)
            sentence_frequency = count_sentence_frequency(all_sentences)
            #print("contador repetidos:",sentence_frequency)
            most_common_sentence = find_most_common_sentence(sentence_frequency)
            #print("Palabra más repetida:", most_common_sentence)
            if most_common_sentence is not None:
                comment_body = "Count me in ^^ @subidu\n" + most_common_sentence

        if post["author"] in autores_preconfig:
            if post["author"] == "USERNAME_2" and "#GivePeaceAChance" in post.body:
                comment_body = "Count me in ^^ @subidu #GivePeaceAChance"
            if post["author"] == "USERNAME_3" and "guess a number between" in post.body:
                numero_aleatorio = random.randint(1, 500)
                comment_body = "Count me in ^^ @subidu {}".format(numero_aleatorio)
            if (
                post["author"] == "USERNAME_4"
                and "choose a number from 1 to 10 depending how much you like that card"
                in post.body
            ):
                comment_body = "Count me in ^^ @subidu. Rating 7"
            if post["author"] == "USERNAME_5" and "WAX adress" in post.body:
                comment_body = "Count me in ^^ @subidu. zzkfm.wam"
            if post["author"] == "USERNAME_6" and "ecency" in post.body.lower():
                comment_body = "Count me in ^^ @subidu. Ecency"
            if (
                post["author"] == "USERNAME_7"
                and "Your job is to guess the exact weight of this coin" in post.body
            ):
                numero_aleatorio = round(random.uniform(6, 9), 2)
                comment_body = "Count me in ^^ @subidu {} g".format(numero_aleatorio)
            if post["author"] == "USERNAME_8" and "atx" in post.body.lower():
                comment_body = "Count me in ^^ @subidu. ATX"

        if usuario_respondio and comment_body == comentario_publicado:
            print(f"\n{usuario_a_verificar} ha respondido a este post.", X)
            continue

        # Generar un permlink único
        comment_permlink = "".join(random.choices(string.digits, k=10))

        if usuario_respondio and comment_body != comentario_publicado:
            comment_permlink = permlink_publicado
            print(
                "\nComentario Modificado.\nComentario original: ",
                comentario_publicado,
                "\nComentario modificado: ",
                comment_body,
            )
            count_post_modificados += 1

        # Crear una instancia de TransactionBuilder
        tx = TransactionBuilder(blockchain_instance=h)
#
        # Agregar la operación de comentario al TransactionBuilder
        tx.appendOps(
            BaseComment(
                **{
                    "parent_author": comment_parent_author,
                    "parent_permlink": comment_parent_permlink,
                    "author": comment_author,
                    "permlink": comment_permlink,
                    "title": comment_title,
                    "body": comment_body,
                }
            )
        )

        # Agregar la clave de posting
        # tx.appendWif(os.getenv("wif_posting_key"))
        tx.appendWif(a)
        # Firmar y transmitir la transacción
        signed_tx = tx.sign()
        broadcast_tx = tx.broadcast(trx_id=True)

        print("*" * 50)
        print("\nComentario creado exitosamente para el post:", post["title"])
        print("\n\nValor de 'body':", broadcast_tx["operations"][0][1]["body"])
        print("*" * 50)

        # Espera 3 segundos
        time.sleep(3)

        # Actualizamos el contados de post publicados
        count_post_publicados += 1

    print("\nNumero de post publicados:", count_post_publicados)
    print("\nNumero de post modificados:", count_post_modificados)

if __name__ == "__main__":
    main()

    # Obtener la lista de publicaciones -> List[Class: Comment]
    posts_generator = d.get_discussions("created", q, limit=2000)

    # Contador de post publicados
    count_post_publicados = 0
    count_post_modificados = 0

    X = 0

    # Cargo la lista de autores con respuestas preconfiguradas
    autores_preconfig = author_preconfig()

    # Iterar sobre el generador
    for post in posts_generator:
        if post["author"] == "imfarhad":
            continue
        if X % 50 == 0:
            print(f"post.items.created: {post['created']}")
        X += 1
        print(X)
        """# Si el autor esta en la lista de baneados salta a la siguiente iteracion
        if author_in_banned_list(post["author"]):
            continue"""

Instruction: Añade una forma de trabajar en paralelo y procesar todos los posts_generator

import pytest
import inspect
import re
import threading
import concurrent.futures
import time
from unittest.mock import patch, MagicMock
from multiprocessing import Manager
from types import ModuleType
from typing import Tuple, List, Dict, Any, Optional

def test_implementation_structure(implementation):
    """Test the overall structure of the implementation - ensuring it maintains the original functionality"""
    impl_name, module = implementation

    # Get all source code from the module to examine
    module_source = ""
    for name, obj in inspect.getmembers(module):
        if inspect.isfunction(obj):
            try:
                module_source += inspect.getsource(obj)
            except (OSError, IOError, TypeError):
                pass  # Skip if can't get source

    # More lenient checks for critical elements - using lowercase for case-insensitive matching
    module_source_lower = module_source.lower()

    # The most critical elements that must be present in some form
    critical_elements = [
        ('subidu', ['subidu', 'usuario_a_verificar']),  # The username might be defined as a variable
        ('comment', ['comment', 'comentario']),  # Comment class or references
        ('get_discussions', ['get_discussions', 'discussions']),  # Function to get discussions
        ('time.sleep', ['time.sleep', 'sleep('])  # Sleep functionality
    ]

    # Check for critical elements with alternatives
    missing_critical = []
    for elem_name, alternatives in critical_elements:
        if not any(alt in module_source_lower for alt in alternatives):
            missing_critical.append(elem_name)

    # Counter patterns that should exist in some form
    counter_patterns = [
        'count', 'counter', 'contador',
        'published', 'publicado',
        'modified', 'modificado',
        '+= 1', 'value +=',
        'return "published"', 'return "modified"'
    ]

    # Check if any counter pattern is found
    has_counter_tracking = any(pattern.lower() in module_source_lower for pattern in counter_patterns)

    # Implementation 3 might be significantly different, so we'll have a special check
    if impl_name == 'original_modified_code2' and has_counter_tracking:
        # For implementation3, we'll be more lenient
        pytest.skip(f"Implementation {impl_name} has a unique structure but includes counter tracking")
    else:
        # If it's missing critical elements and doesn't have counter tracking, it's a problem
        assert not missing_critical or has_counter_tracking, \
            f"Implementation {impl_name} is missing critical elements: {missing_critical}"

def test_parallelization_implementation(implementation):
    """Test if the implementation introduces parallel processing for posts correctly"""
    impl_name, module = implementation

    # Skip test for known sequential implementations
    if impl_name in ['original_code', 'original_modified_code2']:
        pytest.skip(f"Implementation {impl_name} is sequential")

    # Collect all function source codes
    module_source = ""
    for name, obj in inspect.getmembers(module):
        if inspect.isfunction(obj):
            try:
                module_source += inspect.getsource(obj)
            except (OSError, IOError, TypeError):
                pass

    # Stronger set of patterns indicating true parallel handling
    parallel_patterns = [
        'ThreadPoolExecutor',
        'ProcessPoolExecutor',
        'executor.submit(',
        'executor.map(',
        'pool.map(',
        'as_completed',
        'futures = [',
        'futures = {',
        'future.result()',
        'with concurrent.futures',
        'with ThreadPoolExecutor',
        'with ProcessPoolExecutor',
    ]

    # Must use some form of parallel dispatch
    parallel_dispatch_detected = any(pattern in module_source for pattern in parallel_patterns)

    assert parallel_dispatch_detected, (
        f"Implementation {impl_name} does not correctly dispatch posts in parallel"
    )

def test_parallel_processing_function(implementation):
    """Test that the implementation includes a function for processing posts in parallel"""
    impl_name, module = implementation

    # Skip test for implementations known to be sequential
    if impl_name in ['original_code', 'original_modified_code2']:
        pytest.skip(f"Implementation {impl_name} is known to be sequential")

    # Get all source code from the module to examine
    module_source = ""
    for name, obj in inspect.getmembers(module):
        if inspect.isfunction(obj):
            try:
                module_source += inspect.getsource(obj)
            except (OSError, IOError, TypeError):
                pass  # Skip if can't get source

    # Check for a function that processes individual posts
    process_post_fn = None
    for name, obj in inspect.getmembers(module):
        if name in ['process_post', 'process_publication', 'process_item'] and inspect.isfunction(obj):
            process_post_fn = obj
            break

    # If there's no dedicated function, check if process_post is defined inside another function
    if process_post_fn is None:
        # Look for function definition patterns
        nested_function_patterns = [
            r'def\s+process_post',
            r'def\s+process_publication',
            r'def\s+process_item',
            r'lambda\s+post'
        ]

        has_nested_function = any(re.search(pattern, module_source) for pattern in nested_function_patterns)

        if has_nested_function:
            assert True, "Processing function is defined inside another function"
        else:
            # Check if there's any evidence of parallel processing in the module
            parallel_patterns = [
                'ThreadPoolExecutor',
                'ProcessPoolExecutor',
                'executor.submit',
                'executor.map',
                'pool.map',
                'with concurrent.futures',
                'futures = [',
                'futures = {',
                'result()',
                'as_completed'
            ]
            has_parallel_code = any(pattern in module_source for pattern in parallel_patterns)
            assert has_parallel_code, f"Implementation {impl_name} does not have a parallel processing function or equivalent code"
    else:
        # There is a process_post function, so this test passes
        assert True

def test_counter_handling(implementation):
    """Test that counters for published and modified posts are handled correctly in parallel context"""
    impl_name, module = implementation

    # Skip test for implementations that might handle counters differently
    if impl_name in ['original_code', 'original_modified_code1', 'original_modified_code2']:
        pytest.skip(f"Implementation {impl_name} may have alternative counter handling")

    # Get all source code from the module to examine
    module_source = ""
    for name, obj in inspect.getmembers(module):
        if inspect.isfunction(obj):
            try:
                module_source += inspect.getsource(obj)
            except (OSError, IOError, TypeError):
                pass  # Skip if can't get source

    # Check if the implementation has proper counter handling
    # Expanded patterns for thread-safe counter implementations
    thread_safe_patterns = [
        'Manager()',  # multiprocessing.Manager
        'Value(',  # shared counter with Manager
        'Lock()',  # threading.Lock
        'threading.Lock',
        'nonlocal',  # using nonlocal for inner function counters
        'atomic',
        'concurrent.futures.as_completed',  # proper handling of future results
        'counter.value',  # accessing a Value counter
        'published_counter',  # common counter name
        'modified_counter',   # common counter name
        'future.result()',    # gathering result from future that might return counter status
        'lock.',              # using a lock
        'synchronized',       # some kind of synchronization
        'return "published"', # returning status
        'return "modified"'   # returning status
    ]

    thread_safe_counters = any(pattern in module_source for pattern in thread_safe_patterns)

    # Less reliable but still valid approaches
    if not thread_safe_counters:
        less_reliable_patterns = [
            'for future in',  # iterating over futures to collect results
            'with ThreadPoolExecutor',  # At least using a ThreadPoolExecutor
            'published = 0',  # Starting a counter
            'modified = 0',   # Starting a counter
            '+=',             # Incrementing a counter
            'count =',        # Using a counter variable
            'count_',         # Common prefix for counter variables
        ]
        thread_safe_counters = any(pattern in module_source for pattern in less_reliable_patterns)

    assert thread_safe_counters, f"Implementation {impl_name} may not handle counters correctly in a parallel context"

def test_post_iteration_approach(implementation):
    """Test that the implementation iterates and dispatches posts for parallel processing"""
    impl_name, module = implementation

    if impl_name in ['original_code', 'original_modified_code2']:
        pytest.skip(f"Implementation {impl_name} is sequential")

    module_source = ""
    for name, obj in inspect.getmembers(module):
        if inspect.isfunction(obj):
            try:
                module_source += inspect.getsource(obj)
            except (OSError, IOError, TypeError):
                pass

    # Look for strong patterns indicating post dispatch
    patterns = [
        'list(posts_generator)',    # collecting posts first
        'posts_list = list(',        # alternate collection
        'executor.submit(',          # submitting posts
        'executor.map(',             # mapping posts
        'pool.map(',                 # pool map
        'futures = [',               # list of futures
        'as_completed',              # tracking futures completion
        'for future in',             # iterating over finished futures
        'ThreadPoolExecutor',
        'ProcessPoolExecutor',
        'with concurrent.futures'
    ]

    post_parallel_processing_detected = any(pattern in module_source for pattern in patterns)

    assert post_parallel_processing_detected, (
        f"Implementation {impl_name} does not dispatch posts correctly for parallel execution"
    )

def test_global_variable_handling(implementation):
    """Test that the implementation properly handles global/shared variables in parallel context"""
    impl_name, module = implementation

    # Get all source code from the module to examine
    module_source = ""
    for name, obj in inspect.getmembers(module):
        if inspect.isfunction(obj):
            try:
                module_source += inspect.getsource(obj)
            except (OSError, IOError, TypeError):
                pass  # Skip if can't get source

    # Check for patterns indicating proper handling of shared variables
    # This is a general check, so we don't want to be too strict

    # Different approaches for handling shared data
    proper_variable_patterns = [
        # Thread-safe approaches
        'Manager()',  # Using multiprocessing.Manager
        'Value(',  # Using shared values
        'Lock()',  # Using locks
        'threading.Lock',  # Explicit locks
        'nonlocal ',  # Using nonlocal for inner functions

        # Return value approaches
        'return ',  # Returning values rather than modifying globals
        'process_post(',  # Using a separate function
        '.submit(',  # Submitting work to executors

        # Counter variables (might be handled properly)
        'count_',  # Counter variables
        'published_counter',
        'modified_counter',

        # Return status approaches
        'return "published"',  # Returning status
        'return "modified"',
        'future.result()',     # Handling results from futures
    ]

    # For sequential implementations, any approach is okay
    is_sequential = 'ThreadPoolExecutor' not in module_source and 'ProcessPoolExecutor' not in module_source

    # Either the implementation is sequential, or it uses proper variable handling
    assert is_sequential or any(pattern in module_source for pattern in proper_variable_patterns), \
        f"Implementation {impl_name} may not handle shared variables correctly in parallel context"

def test_post_parallel_dispatch(implementation):
    """Ensure that posts_generator or its collected list is used inside parallelized execution."""
    impl_name, module = implementation

    if impl_name in ['original_code', 'original_modified_code2']:
        pytest.skip(f"Implementation {impl_name} is sequential")

    module_source = ""
    for name, obj in inspect.getmembers(module):
        if inspect.isfunction(obj):
            try:
                module_source += inspect.getsource(obj)
            except (OSError, IOError, TypeError):
                pass

    # Stronger patterns: Are posts being mapped or submitted?
    dispatch_patterns = [
        'executor.submit(',         # Submit each post
        'executor.map(',            # Map over posts
        'pool.map(',                # Multiprocessing
        'for post in posts_list',   # Collect first, then parallelize
        'for post in list(posts_generator)', # Materialize generator
    ]

    post_dispatch_detected = any(pattern in module_source for pattern in dispatch_patterns)

    assert post_dispatch_detected, (
        f"Implementation {impl_name} does not dispatch posts_generator posts correctly into parallel tasks."
    )

import pytest
import os
import sys
import json
from typing import Dict, List, Optional, Any

# Import from local test_utils.py in the same directory
from test_utils import TestUtils, TestResultsManager

# Load all implementations in the current sandbox
implementations = TestUtils.load_all_implementations()
test_results = TestResultsManager()

@pytest.fixture(scope="session")
def sandbox_dir():
    """Fixture to provide the sandbox directory path."""
    return os.path.dirname(os.path.abspath(__file__))

@pytest.fixture(scope="session")
def sandbox_name():
    """Fixture to provide the sandbox name."""
    return os.path.basename(os.path.dirname(os.path.abspath(__file__)))

@pytest.fixture(scope="session")
def all_implementations():
    """Fixture to provide all implementations as a dictionary."""
    return implementations

@pytest.fixture(params=list(implementations.items()))
def implementation(request):
    """Fixture to provide each implementation to tests one at a time."""
    return request.param

@pytest.fixture(scope="session")
def results_manager():
    """Fixture to provide access to the test results manager."""
    return test_results

# Hook for collecting test results
@pytest.hookimpl(tryfirst=True, hookwrapper=True)
def pytest_runtest_makereport(item, call):
    """Pytest hook to collect test results."""
    # Execute all other hooks to obtain the report object
    outcome = yield
    rep = outcome.get_result()

    # We're only interested in the call outcome
    if rep.when == "call":
        if hasattr(item, "callspec") and "implementation" in item.callspec.params:
            # Get implementation name and module
            impl_name, _ = item.callspec.params["implementation"]

            # Get test name
            test_name = item.nodeid.split("::")[-1]

            # Record result
            if rep.passed:
                test_results.record_result(impl_name, test_name, True)
            elif rep.failed:
                error_msg = str(rep.longrepr) if rep.longrepr else "Test failed"
                test_results.record_result(impl_name, test_name, False, error_msg)
            elif rep.skipped:
                skip_reason = rep.longrepr[2] if rep.longrepr else "Test skipped"
                test_results.record_skip(impl_name, test_name, skip_reason)

# Hook to save results at the end of testing
@pytest.hookimpl(trylast=True)
def pytest_sessionfinish(session, exitstatus):
    """Save test results at the end of the test session."""
    test_results.save_results()

import os
import sys
import glob
import re
import importlib.util
import traceback
import types
from typing import Dict, List, Optional, Any, Tuple

class TestUtils:
    @staticmethod
    def discover_implementation_files(directory: str = None) -> List[str]:
        """Find all implementation files in the current sandbox directory."""
        if directory is None:
            directory = os.path.dirname(os.path.abspath(__file__))

        patterns = [
            r'modified_code\d+\.py',
            r'new_code\d+\.py',
            r'original_code\.py',
            r'implementation\d*\.py'
        ]

        pattern = re.compile('|'.join(f'({p})' for p in patterns))
        implementations = []

        for file_path in glob.glob(os.path.join(directory, '*.py')):
            if pattern.search(os.path.basename(file_path)):
                implementations.append(file_path)

        # Sort files numerically
        def sort_key(path):
            filename = os.path.basename(path)
            match = re.search(r'(\d+)', filename)
            return int(match.group(1)) if match else 0

        return sorted(implementations, key=sort_key)

    @staticmethod
    def create_mock_module(file_path: str, module_name: str, error_info: str) -> types.ModuleType:
        """Create a mock module that contains error information but can still be tested."""
        # Create a new module object
        mock_module = types.ModuleType(module_name)

        # Add basic attributes
        mock_module.__file__ = file_path
        mock_module.__name__ = module_name
        mock_module.__display_name__ = module_name
        mock_module.__error__ = error_info

        # Add a dummy function that can be detected by test functions
        def dummy_function(*args, **kwargs):
            return f"Error in module: {error_info}"

        setattr(mock_module, "implementation_error", dummy_function)

        return mock_module

    @staticmethod
    def load_module(file_path: str, module_name: Optional[str] = None) -> Any:
        """
        Safely load a module from a file path with proper error handling.
        If the module has errors, return a mock module that can still be tested.
        """
        if module_name is None:
            module_name = os.path.basename(file_path).replace('.py', '')

        # Create a unique module name to avoid conflicts
        sandbox_id = os.path.basename(os.path.dirname(file_path))
        unique_module_name = f"{sandbox_id}_{module_name}"

        try:
            # First, try to read the file to check for syntax errors
            with open(file_path, 'r') as f:
                source_code = f.read()

            # Check for syntax errors by compiling the code
            try:
                compiled = compile(source_code, file_path, 'exec')
            except SyntaxError as e:
                error_msg = f"Syntax error: {str(e)}"
                print(f"Syntax error in {file_path}: {e}")
                print(f"  Line {e.lineno}, column {e.offset}: {e.text}")
                return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

            # Create the module spec
            spec = importlib.util.spec_from_file_location(unique_module_name, file_path)
            if spec is None or spec.loader is None:
                error_msg = f"Could not create spec for {file_path}"
                print(f"Error: {error_msg}")
                return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

            # Create the module object
            module = importlib.util.module_from_spec(spec)
            sys.modules[unique_module_name] = module

            # Special handling for execution errors
            try:
                # Execute the module code in a safe way
                spec.loader.exec_module(module)
                # Store the original name for reference
                module.__display_name__ = module_name
                return module
            except Exception as e:
                error_msg = f"Runtime error: {str(e)}"
                traceback_str = traceback.format_exc()
                print(f"Error executing module {file_path}: {e}")
                print(traceback_str)

                # Create a partial module that contains what we loaded before the error
                mock_module = TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

                # Copy any attributes that might have been defined before the error
                for attr_name in dir(module):
                    if not attr_name.startswith('__'):
                        try:
                            setattr(mock_module, attr_name, getattr(module, attr_name))
                        except Exception:
                            pass  # Skip attributes that can't be copied

                return mock_module

        except FileNotFoundError as e:
            error_msg = f"File not found: {str(e)}"
            print(f"Error: {error_msg}")
            return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)
        except Exception as e:
            error_msg = f"Unexpected error: {str(e)}"
            print(f"Error loading module {file_path}: {e}")
            return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

    @classmethod
    def load_all_implementations(cls, directory: str = None) -> Dict[str, Any]:
        """Load all implementation files in the directory, including those with errors."""
        if directory is None:
            directory = os.path.dirname(os.path.abspath(__file__))

        implementations = {}

        implementation_files = cls.discover_implementation_files(directory)
        if not implementation_files:
            print("WARNING: No implementation files found. Check your file naming patterns.")

        for file_path in implementation_files:
            module_name = os.path.basename(file_path).replace('.py', '')
            module = cls.load_module(file_path, module_name)

            # Always add the module, even if it has errors
            implementations[module_name] = module

            if hasattr(module, '__error__'):
                print(f"Loaded with errors: {module_name} - {module.__error__}")
            else:
                print(f"Successfully loaded: {module_name}")

        return implementations

class TestResultsManager:
    def __init__(self):
        self.results = {}
        self.sandbox_name = os.path.basename(os.path.dirname(os.path.abspath(__file__)))

    def record_result(self, impl_name: str, test_name: str, passed: bool,
                     error_msg: Optional[str] = None) -> None:
        """Record a test result for an implementation."""
        if impl_name not in self.results:
            self.results[impl_name] = {"passed": 0, "failed": 0, "skipped": 0, "errors": []}

        if passed:
            self.results[impl_name]["passed"] += 1
        else:
            self.results[impl_name]["failed"] += 1
            if error_msg:
                self.results[impl_name]["errors"].append({
                    "test": test_name,
                    "error": error_msg
                })

    def record_skip(self, impl_name: str, test_name: str,
                   reason: Optional[str] = None) -> None:
        """Record a skipped test for an implementation."""
        if impl_name not in self.results:
            self.results[impl_name] = {"passed": 0, "failed": 0, "skipped": 0, "errors": []}

        self.results[impl_name]["skipped"] += 1
        if reason:
            self.results[impl_name]["errors"].append({
                "test": test_name,
                "error": f"SKIPPED: {reason}"
            })

    def get_winner(self) -> Tuple[Optional[int], Dict]:
        """Determine the winner based on test results."""
        winner = None
        max_passed = -1

        for impl_name, results in self.results.items():
            if impl_name == "original_code":
                continue  # Skip original code when determining winner

            if results["passed"] > max_passed:
                max_passed = results["passed"]
                winner = impl_name
            # Break ties by looking at failure count
            elif results["passed"] == max_passed and winner is not None:
                if results["failed"] < self.results[winner]["failed"]:
                    winner = impl_name

        # Convert winner to numeric index if possible
        winner_index = -1
        if winner and re.match(r'modified_code\d+', winner):
            try:
                winner_index = int(re.search(r'(\d+)', winner).group(1))
            except (AttributeError, ValueError):
                pass

        return winner_index, self.results

    def save_results(self, filename: str = "test_results.json") -> None:
        """Save test results to a JSON file."""
        import json

        winner_index, results = self.get_winner()

        # Check if all tests were skipped
        all_skipped = all(
            stats["skipped"] == stats["passed"] + stats["failed"] + stats["skipped"]
            for impl_name, stats in results.items()
            if impl_name != "original_code"
        )

        output = {
            "winner": winner_index,
            "all_skipped": all_skipped,
            "results": {
                name: {
                    "passed": stats["passed"],
                    "failed": stats["failed"],
                    "skipped": stats["skipped"],
                    "total": stats["passed"] + stats["failed"] + stats["skipped"]
                }
                for name, stats in results.items()
                if not name.startswith("_")  # Skip internal items
            }
        }

        with open(filename, "w") as f:
            json.dump(output, f, indent=2)

        print(f"Test results saved to {filename}")

        return output


Instruction: create a column name `Frequency` put `117` on every row that has `E16` in `EventId`

import os
import pandas as pd
import pytest
import importlib.util
import inspect
import sys
from io import StringIO
from unittest.mock import patch
import re

def test_dataframe_manipulation(implementation):
    """Test that the implementation correctly adds a Frequency column with value 117 for rows with E16 in EventId"""
    impl_name, module = implementation

    # First, create a test DataFrame with various EventId values
    test_df = pd.DataFrame({
        'EventId': ['E15', 'E16', 'E16-extra', 'E17', 'E160', 'E16_suffix', 'prefix_E16'],
        'Value': [10, 20, 30, 40, 50, 60, 70]
    })

    # Try to determine if this is a function-based implementation
    implementation_type = _detect_implementation_type(module)

    if implementation_type == "function":
        # Find all functions that might operate on DataFrames
        for func_name, func in inspect.getmembers(module, inspect.isfunction):
            # Create a fresh copy of test data for each function
            df_copy = test_df.copy()

            # Call the function with our test DataFrame
            try:
                result = func(df_copy)

                # If the function returns a DataFrame, use that for verification
                if isinstance(result, pd.DataFrame):
                    _verify_results(result)
                else:
                    # Otherwise check if it modified our input DataFrame
                    _verify_results(df_copy)

                # If we found a working implementation, no need to try other functions
                return
            except (TypeError, ValueError, AssertionError):
                # This function didn't work, try the next one
                continue

    # If we didn't find a suitable function or the verification failed,
    # try the script approach (execute the module code directly)
    with patch('builtins.print'):
        # Execute the implementation with our test DataFrame
        df = test_df.copy()

        try:
            # First, try to get and execute the source
            _execute_module_with_df(module, df)
            _verify_results(df)
        except (OSError, AssertionError):
            # If that fails, try the manual approach
            _execute_implementation_pattern(module, df)
            _verify_results(df)

def test_dataframe_creation_and_manipulation(implementation):
    """Test that implementations which create their own DataFrame still work correctly"""
    impl_name, module = implementation

    # Create a dictionary to hold all variables
    namespace = {'pd': pd, 'pandas': pd}

    implementation_type = _detect_implementation_type(module)

    # If it's a script, try to execute it
    if implementation_type == "script":
        try:
            with patch('builtins.print'):
                # Try to load the file directly
                file_path = inspect.getfile(module)
                with open(file_path, 'r') as f:
                    code = f.read()

                # Execute the code with our namespace
                exec(code, namespace)

                # Check if a DataFrame was created
                for name, obj in list(namespace.items()):
                    if isinstance(obj, pd.DataFrame) and 'EventId' in getattr(obj, 'columns', []):
                        try:
                            _verify_results(obj)
                            return  # Success, no need to continue
                        except AssertionError:
                            continue  # Try another DataFrame if this one doesn't match
        except (OSError, SyntaxError, NameError, KeyError):
            # If there was an error, fall back to another approach
            pass

    # If we get here, the previous approach didn't work
    # Try executing it with a predefined DataFrame
    df = pd.DataFrame({
        'EventId': ['E15', 'E16', 'E16-extra', 'E17'],
        'Value': [10, 20, 30, 40]
    })

    try:
        _execute_module_with_df(module, df)
        _verify_results(df)
    except (OSError, AssertionError):
        # If that fails, try the manual approach
        _execute_implementation_pattern(module, df)
        _verify_results(df)

def test_dataframe_with_na_values(implementation):
    """Test handling of NA values in EventId column"""
    impl_name, module = implementation

    # Create a test DataFrame with NA values
    test_df = pd.DataFrame({
        'EventId': ['E15', 'E16', None, pd.NA, 'E16'],
        'Value': [10, 20, 30, 40, 50]
    })

    # Execute the implementation code
    df = test_df.copy()

    with patch('builtins.print'):
        try:
            # Try running the implementation
            _execute_module_with_df(module, df)

            # Verify that rows with 'E16' have Frequency=117
            e16_rows = df[df['EventId'] == 'E16']
            assert not e16_rows.empty, "No rows with EventId = 'E16' found"
            assert all(e16_rows['Frequency'] == 117), "Not all rows with EventId = 'E16' have Frequency = 117"

            # Make sure we have a Frequency column
            assert 'Frequency' in df.columns, "Frequency column was not created"
        except (OSError, AssertionError, NameError, KeyError):
            # If the previous approach failed, try the manual approach
            try:
                _execute_implementation_pattern(module, df)

                # Verify the same conditions
                e16_rows = df[df['EventId'] == 'E16']
                assert not e16_rows.empty, "No rows with EventId = 'E16' found"
                assert all(e16_rows['Frequency'] == 117), "Not all rows with EventId = 'E16' have Frequency = 117"
                assert 'Frequency' in df.columns, "Frequency column was not created"
            except Exception as e:
                # Some implementations might not handle NA values well, that's okay
                # We'll mark this as a pass anyway, but print a note
                print(f"Implementation {impl_name} had issues with NA values: {e}")

def test_implementation_handles_existing_frequency_column(implementation):
    """Test that the implementation correctly handles existing Frequency column"""
    impl_name, module = implementation

    # Create a test DataFrame with an existing Frequency column
    test_df = pd.DataFrame({
        'EventId': ['E15', 'E16', 'E17', 'E16'],
        'Value': [10, 20, 30, 40],
        'Frequency': [1, 2, 3, 4]
    })

    # Make a copy for testing
    df = test_df.copy()

    with patch('builtins.print'):
        try:
            # Try running the implementation
            _execute_module_with_df(module, df)

            # Verify that rows with 'E16' have been updated to Frequency=117
            e16_rows = df[df['EventId'] == 'E16']
            assert not e16_rows.empty, "No rows with EventId = 'E16' found"
            assert all(e16_rows['Frequency'] == 117), "Not all rows with EventId = 'E16' have Frequency = 117"

            # Check that other rows maintained their original values
            non_e16_rows = df[df['EventId'] != 'E16']
            original_non_e16 = test_df[test_df['EventId'] != 'E16']

            if not non_e16_rows.empty:
                for i in range(len(non_e16_rows)):
                    if i < len(original_non_e16):
                        assert non_e16_rows.iloc[i]['Frequency'] == original_non_e16.iloc[i]['Frequency'], \
                            f"Row {i} has incorrect Frequency value"
        except (OSError, AssertionError):
            # If that fails, try the manual approach
            try:
                _execute_implementation_pattern(module, df)

                # Verify the same conditions
                e16_rows = df[df['EventId'] == 'E16']
                assert not e16_rows.empty, "No rows with EventId = 'E16' found"
                assert all(e16_rows['Frequency'] == 117), "Not all rows with EventId = 'E16' have Frequency = 117"

                # Check that other rows maintained their original values
                non_e16_rows = df[df['EventId'] != 'E16']
                original_non_e16 = test_df[test_df['EventId'] != 'E16']

                if not non_e16_rows.empty:
                    for i in range(len(non_e16_rows)):
                        if i < len(original_non_e16):
                            assert non_e16_rows.iloc[i]['Frequency'] == original_non_e16.iloc[i]['Frequency'], \
                                f"Row {i} has incorrect Frequency value"
            except Exception as e:
                # If all approaches fail, the implementation likely doesn't handle existing Frequency columns
                pytest.fail(f"Implementation {impl_name} failed with existing Frequency column: {e}")

def _detect_implementation_type(module):
    """Detect whether the implementation is function-based or script-based"""
    functions = inspect.getmembers(module, inspect.isfunction)

    # If there are functions defined, it's likely function-based
    if functions:
        return "function"
    else:
        return "script"

def _execute_module_with_df(module, df):
    """Try to execute a module with a provided DataFrame"""
    try:
        # Try to get the source code
        source = inspect.getsource(module)
        # Execute it with our test DataFrame
        exec(source, {'df': df, 'pd': pd, 'pandas': pd})
    except OSError:
        # If we can't get the source code, try to read the file directly
        file_path = inspect.getfile(module)
        with open(file_path, 'r') as f:
            source = f.read()
        # Execute it with our test DataFrame
        exec(source, {'df': df, 'pd': pd, 'pandas': pd})

def _execute_implementation_pattern(module, df):
    """Try to execute common implementation patterns directly"""

    # Implementation pattern 1: Using loc with contains
    df.loc[df['EventId'].str.contains('E16', na=False), 'Frequency'] = 117

    # If that didn't work (no Frequency column created), try pattern 2
    if 'Frequency' not in df.columns:
        df['Frequency'] = df.apply(lambda row: 117 if row['EventId'] == 'E16' else None, axis=1)

    # If that didn't work either, try pattern 3
    if df[df['EventId'] == 'E16']['Frequency'].isna().any():
        df.loc[df['EventId'] == 'E16', 'Frequency'] = 117

def _verify_results(df):
    """Helper function to verify the results of the implementations"""
    # Check that a Frequency column was added
    assert 'Frequency' in df.columns, "Frequency column was not created"

    # Check that rows with exactly 'E16' as EventId have Frequency=117
    e16_rows = df[df['EventId'] == 'E16']
    assert not e16_rows.empty, "No rows with EventId = 'E16' found"
    assert all(e16_rows['Frequency'] == 117), "Not all rows with EventId = 'E16' have Frequency = 117"

    # Depending on the implementation, there are two valid interpretations:
    # 1. Only exact 'E16' matches get 117 (strict equality)
    # 2. Any string containing 'E16' gets 117 (contains match)

    # Let's check which approach the implementation used
    contains_e16 = df[df['EventId'].str.contains('E16', na=False)]
    exact_e16 = df[df['EventId'] == 'E16']

    # If all rows containing 'E16' have Frequency=117, it's using the 'contains' approach
    if len(contains_e16) > len(exact_e16):
        try:
            assert all(contains_e16['Frequency'] == 117), \
                "Not all rows containing 'E16' have Frequency = 117"
        except (AssertionError, KeyError):
            # It might be using exact matches, so that's okay
            pass

import pytest
import os
import sys
import json
from typing import Dict, List, Optional, Any

# Import from local test_utils.py in the same directory
from test_utils import TestUtils, TestResultsManager

# Load all implementations in the current sandbox
implementations = TestUtils.load_all_implementations()
test_results = TestResultsManager()

@pytest.fixture(scope="session")
def sandbox_dir():
    """Fixture to provide the sandbox directory path."""
    return os.path.dirname(os.path.abspath(__file__))

@pytest.fixture(scope="session")
def sandbox_name():
    """Fixture to provide the sandbox name."""
    return os.path.basename(os.path.dirname(os.path.abspath(__file__)))

@pytest.fixture(scope="session")
def all_implementations():
    """Fixture to provide all implementations as a dictionary."""
    return implementations

@pytest.fixture(params=list(implementations.items()))
def implementation(request):
    """Fixture to provide each implementation to tests one at a time."""
    return request.param

@pytest.fixture(scope="session")
def results_manager():
    """Fixture to provide access to the test results manager."""
    return test_results

# Hook for collecting test results
@pytest.hookimpl(tryfirst=True, hookwrapper=True)
def pytest_runtest_makereport(item, call):
    """Pytest hook to collect test results."""
    # Execute all other hooks to obtain the report object
    outcome = yield
    rep = outcome.get_result()

    # We're only interested in the call outcome
    if rep.when == "call":
        if hasattr(item, "callspec") and "implementation" in item.callspec.params:
            # Get implementation name and module
            impl_name, _ = item.callspec.params["implementation"]

            # Get test name
            test_name = item.nodeid.split("::")[-1]

            # Record result
            if rep.passed:
                test_results.record_result(impl_name, test_name, True)
            elif rep.failed:
                error_msg = str(rep.longrepr) if rep.longrepr else "Test failed"
                test_results.record_result(impl_name, test_name, False, error_msg)
            elif rep.skipped:
                skip_reason = rep.longrepr[2] if rep.longrepr else "Test skipped"
                test_results.record_skip(impl_name, test_name, skip_reason)

# Hook to save results at the end of testing
@pytest.hookimpl(trylast=True)
def pytest_sessionfinish(session, exitstatus):
    """Save test results at the end of the test session."""
    test_results.save_results()

import os
import sys
import glob
import re
import importlib.util
import traceback
import types
from typing import Dict, List, Optional, Any, Tuple

class TestUtils:
    @staticmethod
    def discover_implementation_files(directory: str = None) -> List[str]:
        """Find all implementation files in the current sandbox directory."""
        if directory is None:
            directory = os.path.dirname(os.path.abspath(__file__))

        patterns = [
            r'modified_code\d+\.py',
            r'new_code\d+\.py',
            r'original_code\.py',
            r'implementation\d*\.py'
        ]

        pattern = re.compile('|'.join(f'({p})' for p in patterns))
        implementations = []

        for file_path in glob.glob(os.path.join(directory, '*.py')):
            if pattern.search(os.path.basename(file_path)):
                implementations.append(file_path)

        # Sort files numerically
        def sort_key(path):
            filename = os.path.basename(path)
            match = re.search(r'(\d+)', filename)
            return int(match.group(1)) if match else 0

        return sorted(implementations, key=sort_key)

    @staticmethod
    def create_mock_module(file_path: str, module_name: str, error_info: str) -> types.ModuleType:
        """Create a mock module that contains error information but can still be tested."""
        # Create a new module object
        mock_module = types.ModuleType(module_name)

        # Add basic attributes
        mock_module.__file__ = file_path
        mock_module.__name__ = module_name
        mock_module.__display_name__ = module_name
        mock_module.__error__ = error_info

        # Add a dummy function that can be detected by test functions
        def dummy_function(*args, **kwargs):
            return f"Error in module: {error_info}"

        setattr(mock_module, "implementation_error", dummy_function)

        return mock_module

    @staticmethod
    def load_module(file_path: str, module_name: Optional[str] = None) -> Any:
        """
        Safely load a module from a file path with proper error handling.
        If the module has errors, return a mock module that can still be tested.
        """
        if module_name is None:
            module_name = os.path.basename(file_path).replace('.py', '')

        # Create a unique module name to avoid conflicts
        sandbox_id = os.path.basename(os.path.dirname(file_path))
        unique_module_name = f"{sandbox_id}_{module_name}"

        try:
            # First, try to read the file to check for syntax errors
            with open(file_path, 'r') as f:
                source_code = f.read()

            # Check for syntax errors by compiling the code
            try:
                compiled = compile(source_code, file_path, 'exec')
            except SyntaxError as e:
                error_msg = f"Syntax error: {str(e)}"
                print(f"Syntax error in {file_path}: {e}")
                print(f"  Line {e.lineno}, column {e.offset}: {e.text}")
                return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

            # Create the module spec
            spec = importlib.util.spec_from_file_location(unique_module_name, file_path)
            if spec is None or spec.loader is None:
                error_msg = f"Could not create spec for {file_path}"
                print(f"Error: {error_msg}")
                return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

            # Create the module object
            module = importlib.util.module_from_spec(spec)
            sys.modules[unique_module_name] = module

            # Special handling for execution errors
            try:
                # Execute the module code in a safe way
                spec.loader.exec_module(module)
                # Store the original name for reference
                module.__display_name__ = module_name
                return module
            except Exception as e:
                error_msg = f"Runtime error: {str(e)}"
                traceback_str = traceback.format_exc()
                print(f"Error executing module {file_path}: {e}")
                print(traceback_str)

                # Create a partial module that contains what we loaded before the error
                mock_module = TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

                # Copy any attributes that might have been defined before the error
                for attr_name in dir(module):
                    if not attr_name.startswith('__'):
                        try:
                            setattr(mock_module, attr_name, getattr(module, attr_name))
                        except Exception:
                            pass  # Skip attributes that can't be copied

                return mock_module

        except FileNotFoundError as e:
            error_msg = f"File not found: {str(e)}"
            print(f"Error: {error_msg}")
            return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)
        except Exception as e:
            error_msg = f"Unexpected error: {str(e)}"
            print(f"Error loading module {file_path}: {e}")
            return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

    @classmethod
    def load_all_implementations(cls, directory: str = None) -> Dict[str, Any]:
        """Load all implementation files in the directory, including those with errors."""
        if directory is None:
            directory = os.path.dirname(os.path.abspath(__file__))

        implementations = {}

        implementation_files = cls.discover_implementation_files(directory)
        if not implementation_files:
            print("WARNING: No implementation files found. Check your file naming patterns.")

        for file_path in implementation_files:
            module_name = os.path.basename(file_path).replace('.py', '')
            module = cls.load_module(file_path, module_name)

            # Always add the module, even if it has errors
            implementations[module_name] = module

            if hasattr(module, '__error__'):
                print(f"Loaded with errors: {module_name} - {module.__error__}")
            else:
                print(f"Successfully loaded: {module_name}")

        return implementations

class TestResultsManager:
    def __init__(self):
        self.results = {}
        self.sandbox_name = os.path.basename(os.path.dirname(os.path.abspath(__file__)))

    def record_result(self, impl_name: str, test_name: str, passed: bool,
                     error_msg: Optional[str] = None) -> None:
        """Record a test result for an implementation."""
        if impl_name not in self.results:
            self.results[impl_name] = {"passed": 0, "failed": 0, "skipped": 0, "errors": []}

        if passed:
            self.results[impl_name]["passed"] += 1
        else:
            self.results[impl_name]["failed"] += 1
            if error_msg:
                self.results[impl_name]["errors"].append({
                    "test": test_name,
                    "error": error_msg
                })

    def record_skip(self, impl_name: str, test_name: str,
                   reason: Optional[str] = None) -> None:
        """Record a skipped test for an implementation."""
        if impl_name not in self.results:
            self.results[impl_name] = {"passed": 0, "failed": 0, "skipped": 0, "errors": []}

        self.results[impl_name]["skipped"] += 1
        if reason:
            self.results[impl_name]["errors"].append({
                "test": test_name,
                "error": f"SKIPPED: {reason}"
            })

    def get_winner(self) -> Tuple[Optional[int], Dict]:
        """Determine the winner based on test results."""
        winner = None
        max_passed = -1

        for impl_name, results in self.results.items():
            if impl_name == "original_code":
                continue  # Skip original code when determining winner

            if results["passed"] > max_passed:
                max_passed = results["passed"]
                winner = impl_name
            # Break ties by looking at failure count
            elif results["passed"] == max_passed and winner is not None:
                if results["failed"] < self.results[winner]["failed"]:
                    winner = impl_name

        # Convert winner to numeric index if possible
        winner_index = -1
        if winner and re.match(r'modified_code\d+', winner):
            try:
                winner_index = int(re.search(r'(\d+)', winner).group(1))
            except (AttributeError, ValueError):
                pass

        return winner_index, self.results

    def save_results(self, filename: str = "test_results.json") -> None:
        """Save test results to a JSON file."""
        import json

        winner_index, results = self.get_winner()

        # Check if all tests were skipped
        all_skipped = all(
            stats["skipped"] == stats["passed"] + stats["failed"] + stats["skipped"]
            for impl_name, stats in results.items()
            if impl_name != "original_code"
        )

        output = {
            "winner": winner_index,
            "all_skipped": all_skipped,
            "results": {
                name: {
                    "passed": stats["passed"],
                    "failed": stats["failed"],
                    "skipped": stats["skipped"],
                    "total": stats["passed"] + stats["failed"] + stats["skipped"]
                }
                for name, stats in results.items()
                if not name.startswith("_")  # Skip internal items
            }
        }

        with open(filename, "w") as f:
            json.dump(output, f, indent=2)

        print(f"Test results saved to {filename}")

        return output


import requests

def interact_with_local_llm(prompt, base_url="http://localhost:11434"):
    """
    Interact with a local LLM using the Ollama API.

    :param prompt: The input prompt for the LLM.
    :param base_url: The base URL of the Ollama API.
    :return: The response from the LLM.
    """
    endpoint = f"{base_url}/api/generate"
    payload = {
        "model": "llama3.2:latest",  # Replace with your model name
        "prompt": prompt,
        "max_tokens": 2048  # Adjust as needed
    }
    headers = {
        "Content-Type": "application/json"
    }

    try:
        response = requests.post(endpoint, json=payload, headers=headers)
        response.raise_for_status()
        return response.json().get('response', '')
    except requests.exceptions.RequestException as e:

        return None

# Example usage
if __name__ == "__main__":
    prompt = "Hello, how are you?"
    response = interact_with_local_llm(prompt)
    if response:
        print(f"LLM Response: {response}")

Instruction: An error occurred: Extra data: line 2 column 1 (char 101)

import json
import pytest
import requests
from unittest import mock
import inspect
import os

def test_implementation_handles_json_decode_error(implementation):
    """Test if implementation can handle JSON responses with multiple lines properly."""
    impl_name, module = implementation

    # Find or create the function to test
    test_function = _get_testable_function(module, impl_name)

    # Mock responses with multiple JSON objects, simulating the error case
    mock_response = mock.Mock()
    mock_response.status_code = 200
    mock_response.text = '{"response": "Hello"}\n{"response": " world!"}'
    mock_response.raise_for_status.return_value = None

    # Some implementations may use response.iter_lines()
    mock_response.iter_lines.return_value = [
        b'{"response": "Hello"}',
        b'{"response": " world!"}',
    ]

    # Some implementations may try to use json() directly, which would fail
    # with multiple JSON objects, so we need to handle this appropriately
    def json_side_effect():
        try:
            return json.loads(mock_response.text)
        except json.JSONDecodeError:
            # Return the first JSON object
            return json.loads('{"response": "Hello"}')

    mock_response.json.side_effect = json_side_effect

    with mock.patch("requests.post", return_value=mock_response):
        # Call the implementation but catch exceptions
        try:
            result = test_function("Test prompt")

            # The implementation should either return some result or None if it can't handle this
            if result is None:
                pytest.skip(
                    f"{impl_name} doesn't handle multi-line JSON, but this might be acceptable"
                )
            else:
                # Some part of the response should be there
                assert "Hello" in str(result) or "world" in str(
                    result
                ), f"{impl_name} doesn't extract useful content from multi-line JSON"
        except Exception as e:
            pytest.fail(f"{impl_name} throws exception with multi-line JSON: {str(e)}")

def test_implementation_with_valid_single_json_response(implementation):
    """Test if implementation works with normal JSON responses."""
    impl_name, module = implementation

    # Skip if module has syntax errors
    if _has_syntax_error(module):
        pytest.skip(f"Implementation {impl_name} has syntax errors")

    # Find or create the function to test
    test_function = _get_testable_function(module, impl_name)

    # Mock a normal single JSON response
    mock_response = mock.Mock()
    mock_response.status_code = 200
    mock_response.text = '{"response": "Normal response"}'
    mock_response.raise_for_status.return_value = None

    # For implementations using json() method directly
    mock_response.json.return_value = {"response": "Normal response"}

    # For implementations using iter_lines()
    mock_response.iter_lines.return_value = [b'{"response": "Normal response"}']

    with mock.patch("requests.post", return_value=mock_response):
        try:
            result = test_function("Test prompt")

            assert result is not None, f"{impl_name} fails with valid JSON response"
            # Either the implementation returns the exact response or handles it in some way
            assert (
                "Normal response" in str(result) or result != ""
            ), f"{impl_name} doesn't properly extract response"
        except Exception as e:
            pytest.fail(f"{impl_name} throws exception with valid JSON: {str(e)}")

def test_implementation_handles_request_errors(implementation):
    """Test if implementation gracefully handles request errors."""
    impl_name, module = implementation

    # Skip if module has syntax errors
    if _has_syntax_error(module):
        pytest.skip(f"Implementation {impl_name} has syntax errors")

    # Find or create the function to test
    test_function = _get_testable_function(module, impl_name)

    with mock.patch(
        "requests.post", side_effect=requests.exceptions.RequestException("Test error")
    ):
        try:
            # Should handle exceptions gracefully and return None
            result = test_function("Test prompt")
            assert (
                result is None
            ), f"{impl_name} doesn't handle request exceptions properly"
        except Exception as e:
            pytest.fail(f"{impl_name} doesn't catch network errors properly: {str(e)}")

def test_implementation_honors_api_parameters(implementation):
    """Test if implementation correctly sends API parameters."""
    impl_name, module = implementation

    # Skip if module has syntax errors
    if _has_syntax_error(module):
        pytest.skip(f"Implementation {impl_name} has syntax errors")

    # Find or create the function to test
    test_function = _get_testable_function(module, impl_name)

    mock_response = mock.Mock()
    mock_response.status_code = 200
    mock_response.text = '{"response": "Test"}'
    mock_response.json.return_value = {"response": "Test"}
    mock_response.raise_for_status.return_value = None
    mock_response.iter_lines.return_value = [b'{"response": "Test"}']

    with mock.patch("requests.post", return_value=mock_response) as mock_post:
        try:
            # Call with custom base_url if supported
            sig = inspect.signature(test_function)
            if "base_url" in sig.parameters:
                test_function("Custom prompt", base_url="http://test-url:8080")
            else:
                test_function("Custom prompt")

            # Implementations might structure their requests differently
            # Some might not call requests.post directly
            if mock_post.call_count == 0:
                pytest.skip(
                    f"{impl_name} might use a different HTTP library or call pattern"
                )
                return

            # Check if payload contains expected data
            args, kwargs = mock_post.call_args

            # Validate URL if available
            if args and len(args) > 0:
                assert "http://" in args[0], f"{impl_name} doesn't use a proper URL"

            # Check payload
            payload = kwargs.get("json", {})
            assert (
                payload.get("prompt") == "Custom prompt"
            ), f"{impl_name} doesn't set prompt correctly"
            assert "model" in payload, f"{impl_name} doesn't set model parameter"
        except Exception as e:
            pytest.fail(f"{impl_name} has issues with API parameters: {str(e)}")

def test_implementation_handles_streaming_format(implementation):
    """Test if implementation correctly handles Ollama streaming format responses."""
    impl_name, module = implementation

    # Skip if module has syntax errors
    if _has_syntax_error(module):
        pytest.skip(f"Implementation {impl_name} has syntax errors")

    # Find or create the function to test
    test_function = _get_testable_function(module, impl_name)

    # This is a common format for LLM streaming responses with multiple JSON objects
    streaming_text = (
        '{"response":"Hello"}\n' '{"response":" there"}\n' '{"response":"!"}'
    )

    mock_response = mock.Mock()
    mock_response.status_code = 200
    mock_response.text = streaming_text
    mock_response.raise_for_status.return_value = None

    # For implementations using json() method directly (will use first object)
    mock_response.json.return_value = {"response": "Hello"}

    # For implementations that use iter_lines() or similar
    mock_response.iter_lines.return_value = [
        b'{"response":"Hello"}',
        b'{"response":" there"}',
        b'{"response":"!"}',
    ]

    with mock.patch("requests.post", return_value=mock_response):
        try:
            result = test_function("Test prompt")

            # We're more lenient here - if the implementation cannot handle
            # streaming format, we'll skip rather than fail
            if result is None:
                pytest.skip(f"{impl_name} doesn't support streaming format")
            else:
                # There should be some content from the response
                assert any(
                    word in str(result) for word in ["Hello", "there", "!"]
                ), f"{impl_name} doesn't extract content from streaming response"
        except Exception as e:
            pytest.fail(f"{impl_name} throws exception with streaming format: {str(e)}")

def test_implementation_addresses_original_issue(implementation):
    """Test if implementation addresses the original 'Extra data' JSON parse error."""
    impl_name, module = implementation

    # Skip if module has syntax errors
    if _has_syntax_error(module):
        pytest.skip(f"Implementation {impl_name} has syntax errors")

    # Check if code structure suggests improved JSON handling
    has_proper_json_handling = False

    # Look for evidence of proper handling in the implementation
    module_path = getattr(module, "__file__", None)
    if module_path and os.path.exists(module_path):
        try:
            with open(module_path, "r") as file:
                code = file.read()

                # More comprehensive checks for proper handling methods
                if (
                    # Common ways to handle streaming JSON responses
                    (
                        "json.loads" in code
                        and any(
                            x in code
                            for x in ["strip().split", "splitlines", "for line in"]
                        )
                    )
                    or
                    # Explicit JSON error handling
                    ("JSONDecodeError" in code and "except" in code)
                    or
                    # General error handling that would catch JSON errors
                    (
                        "except" in code
                        and any(x in code for x in ["ValueError", "Exception"])
                    )
                    or
                    # Proper error logging
                    ("An error occurred" in code and "print" in code)
                    or
                    # Alternative implementation that avoids the issue
                    ("get('response'" in code or "get('response'" in code)
                    or
                    # Handling for response.iter_lines()
                    ("iter_lines" in code)
                ):
                    has_proper_json_handling = True
        except Exception:
            # If we can't read the file, we'll assume it's adequate
            has_proper_json_handling = True
    else:
        # If we can't find a file path, we'll assume it's adequate
        has_proper_json_handling = True

    # The implementation should have some form of improved error handling
    assert (
        has_proper_json_handling
    ), f"{impl_name} doesn't address the original 'Extra data' JSON error"

def test_implementation_gracefully_handles_broken_json(implementation):
    """Test if implementation gracefully handles various types of broken JSON responses."""
    impl_name, module = implementation

    # Find or create the function to test
    test_function = _get_testable_function(module, impl_name)

    # Create a list of broken JSON scenarios to test
    broken_json_scenarios = [
        # Truncated JSON
        '{"response": "Incomplete response',
        # Invalid JSON syntax
        '{"response": "Invalid syntax" "extra": "field"}',
        # Unexpected end of data
        '{"response": "Unexpected end"}{"more": ',
        # Multiple JSON objects with errors
        '{"response": "First part"}\n{"bad_format", "second_part"}',
        # Valid JSON followed by garbage
        '{"response": "Valid part"} GARBAGE DATA',
        # Empty response
        "",
        # Non-JSON response
        "Plain text response with no JSON format",
    ]

    for i, broken_json in enumerate(broken_json_scenarios):
        # Mock response with broken JSON
        mock_response = mock.Mock()
        mock_response.status_code = 200
        mock_response.text = broken_json
        mock_response.raise_for_status.return_value = None

        # For json() method, simulate a JSONDecodeError
        mock_response.json.side_effect = json.JSONDecodeError(
            msg=f"Test JSON error in scenario {i}", doc=broken_json, pos=0
        )

        with mock.patch("requests.post", return_value=mock_response):
            try:
                # Call the implementation with the broken JSON scenario
                result = test_function("Test prompt with broken JSON")

                # We should either get None or some fallback result
                # The key is that it shouldn't crash with an uncaught exception
                assert result is None or isinstance(
                    result, (str, dict)
                ), f"{impl_name} doesn't gracefully handle broken JSON scenario {i}: {broken_json[:20]}..."

            except Exception as e:
                pytest.fail(
                    f"{impl_name} throws uncaught exception with broken JSON scenario {i}: {str(e)}"
                )

def test_implementation_function_signature(implementation):
    """Test if the implementation has a proper function for LLM interaction."""
    impl_name, module = implementation

    # Skip if module has syntax errors
    if _has_syntax_error(module):
        pytest.skip(f"Implementation {impl_name} has syntax errors")

    # Look for appropriate functions
    llm_function = _find_llm_function(module)

    # Some implementations might have a special structure
    if not hasattr(module, llm_function):
        # Try to find any callable attribute
        for name in dir(module):
            if not name.startswith("__") and callable(getattr(module, name)):
                llm_function = name
                break

    # If we still can't find a function, just skip this test
    if not hasattr(module, llm_function):
        pytest.skip(f"Cannot find testable function in {impl_name}")
        return

    # Get the function
    function = getattr(module, llm_function)

    # Try to inspect the function
    try:
        sig = inspect.signature(function)

        # Check for parameters
        parameters = list(sig.parameters.keys())
        assert len(parameters) >= 1, f"{impl_name} function has too few parameters"

        # Check specifically for prompt parameter or at least one positional parameter
        has_prompt_param = "prompt" in sig.parameters
        has_positional = any(
            param.kind == inspect.Parameter.POSITIONAL_OR_KEYWORD
            for param in sig.parameters.values()
        )

        assert (
            has_prompt_param or has_positional
        ), f"{impl_name} is missing appropriate parameters"
    except (ValueError, TypeError):
        # If we can't inspect, we'll skip this check
        pytest.skip(f"Cannot inspect function signature for {impl_name}")

def _has_syntax_error(module):
    """Check if the module has syntax errors by examining its string representation."""
    module_str = str(module)
    return "Syntax error" in module_str or "Error in module" in module_str

def _get_testable_function(module, impl_name):
    """
    Find a function in the module that can be tested or create an adapter function.
    Returns a callable function.
    """
    # If the module has syntax errors, create a dummy function that returns the error
    if _has_syntax_error(module):
        return lambda *args, **kwargs: str(module)

    # Try to find a proper LLM function
    function_name = _find_llm_function(module)

    if function_name and hasattr(module, function_name):
        # Return the actual function
        return getattr(module, function_name)
    else:
        assert False

def _find_llm_function(module):
    """
    Find the LLM interaction function in a module.
    Returns the function name or None if not found.
    """

    # Only check for interact_with_local_llm function
    if hasattr(module, "interact_with_local_llm") and callable(
        getattr(module, "interact_with_local_llm")
    ):
        return "interact_with_local_llm"

    return None

import pytest
import os
import sys
import json
from typing import Dict, List, Optional, Any

# Import from local test_utils.py in the same directory
from test_utils import TestUtils, TestResultsManager

# Load all implementations in the current sandbox
implementations = TestUtils.load_all_implementations()
test_results = TestResultsManager()

@pytest.fixture(scope="session")
def sandbox_dir():
    """Fixture to provide the sandbox directory path."""
    return os.path.dirname(os.path.abspath(__file__))

@pytest.fixture(scope="session")
def sandbox_name():
    """Fixture to provide the sandbox name."""
    return os.path.basename(os.path.dirname(os.path.abspath(__file__)))

@pytest.fixture(scope="session")
def all_implementations():
    """Fixture to provide all implementations as a dictionary."""
    return implementations

@pytest.fixture(params=list(implementations.items()))
def implementation(request):
    """Fixture to provide each implementation to tests one at a time."""
    return request.param

@pytest.fixture(scope="session")
def results_manager():
    """Fixture to provide access to the test results manager."""
    return test_results

# Hook for collecting test results
@pytest.hookimpl(tryfirst=True, hookwrapper=True)
def pytest_runtest_makereport(item, call):
    """Pytest hook to collect test results."""
    # Execute all other hooks to obtain the report object
    outcome = yield
    rep = outcome.get_result()

    # We're only interested in the call outcome
    if rep.when == "call":
        if hasattr(item, "callspec") and "implementation" in item.callspec.params:
            # Get implementation name and module
            impl_name, _ = item.callspec.params["implementation"]

            # Get test name
            test_name = item.nodeid.split("::")[-1]

            # Record result
            if rep.passed:
                test_results.record_result(impl_name, test_name, True)
            elif rep.failed:
                error_msg = str(rep.longrepr) if rep.longrepr else "Test failed"
                test_results.record_result(impl_name, test_name, False, error_msg)
            elif rep.skipped:
                skip_reason = rep.longrepr[2] if rep.longrepr else "Test skipped"
                test_results.record_skip(impl_name, test_name, skip_reason)

# Hook to save results at the end of testing
@pytest.hookimpl(trylast=True)
def pytest_sessionfinish(session, exitstatus):
    """Save test results at the end of the test session."""
    test_results.save_results()

import os
import sys
import glob
import re
import importlib.util
import traceback
import types
from typing import Dict, List, Optional, Any, Tuple

class TestUtils:
    @staticmethod
    def discover_implementation_files(directory: str = None) -> List[str]:
        """Find all implementation files in the current sandbox directory."""
        if directory is None:
            directory = os.path.dirname(os.path.abspath(__file__))

        patterns = [
            r'modified_code\d+\.py',
            r'new_code\d+\.py',
            r'original_code\.py',
            r'implementation\d*\.py'
        ]

        pattern = re.compile('|'.join(f'({p})' for p in patterns))
        implementations = []

        for file_path in glob.glob(os.path.join(directory, '*.py')):
            if pattern.search(os.path.basename(file_path)):
                implementations.append(file_path)

        # Sort files numerically
        def sort_key(path):
            filename = os.path.basename(path)
            match = re.search(r'(\d+)', filename)
            return int(match.group(1)) if match else 0

        return sorted(implementations, key=sort_key)

    @staticmethod
    def create_mock_module(file_path: str, module_name: str, error_info: str) -> types.ModuleType:
        """Create a mock module that contains error information but can still be tested."""
        # Create a new module object
        mock_module = types.ModuleType(module_name)

        # Add basic attributes
        mock_module.__file__ = file_path
        mock_module.__name__ = module_name
        mock_module.__display_name__ = module_name
        mock_module.__error__ = error_info

        # Add a dummy function that can be detected by test functions
        def dummy_function(*args, **kwargs):
            return f"Error in module: {error_info}"

        setattr(mock_module, "implementation_error", dummy_function)

        return mock_module

    @staticmethod
    def load_module(file_path: str, module_name: Optional[str] = None) -> Any:
        """
        Safely load a module from a file path with proper error handling.
        If the module has errors, return a mock module that can still be tested.
        """
        if module_name is None:
            module_name = os.path.basename(file_path).replace('.py', '')

        # Create a unique module name to avoid conflicts
        sandbox_id = os.path.basename(os.path.dirname(file_path))
        unique_module_name = f"{sandbox_id}_{module_name}"

        try:
            # First, try to read the file to check for syntax errors
            with open(file_path, 'r') as f:
                source_code = f.read()

            # Check for syntax errors by compiling the code
            try:
                compiled = compile(source_code, file_path, 'exec')
            except SyntaxError as e:
                error_msg = f"Syntax error: {str(e)}"
                print(f"Syntax error in {file_path}: {e}")
                print(f"  Line {e.lineno}, column {e.offset}: {e.text}")
                return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

            # Create the module spec
            spec = importlib.util.spec_from_file_location(unique_module_name, file_path)
            if spec is None or spec.loader is None:
                error_msg = f"Could not create spec for {file_path}"
                print(f"Error: {error_msg}")
                return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

            # Create the module object
            module = importlib.util.module_from_spec(spec)
            sys.modules[unique_module_name] = module

            # Special handling for execution errors
            try:
                # Execute the module code in a safe way
                spec.loader.exec_module(module)
                # Store the original name for reference
                module.__display_name__ = module_name
                return module
            except Exception as e:
                error_msg = f"Runtime error: {str(e)}"
                traceback_str = traceback.format_exc()
                print(f"Error executing module {file_path}: {e}")
                print(traceback_str)

                # Create a partial module that contains what we loaded before the error
                mock_module = TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

                # Copy any attributes that might have been defined before the error
                for attr_name in dir(module):
                    if not attr_name.startswith('__'):
                        try:
                            setattr(mock_module, attr_name, getattr(module, attr_name))
                        except Exception:
                            pass  # Skip attributes that can't be copied

                return mock_module

        except FileNotFoundError as e:
            error_msg = f"File not found: {str(e)}"
            print(f"Error: {error_msg}")
            return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)
        except Exception as e:
            error_msg = f"Unexpected error: {str(e)}"
            print(f"Error loading module {file_path}: {e}")
            return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

    @classmethod
    def load_all_implementations(cls, directory: str = None) -> Dict[str, Any]:
        """Load all implementation files in the directory, including those with errors."""
        if directory is None:
            directory = os.path.dirname(os.path.abspath(__file__))

        implementations = {}

        implementation_files = cls.discover_implementation_files(directory)
        if not implementation_files:
            print("WARNING: No implementation files found. Check your file naming patterns.")

        for file_path in implementation_files:
            module_name = os.path.basename(file_path).replace('.py', '')
            module = cls.load_module(file_path, module_name)

            # Always add the module, even if it has errors
            implementations[module_name] = module

            if hasattr(module, '__error__'):
                print(f"Loaded with errors: {module_name} - {module.__error__}")
            else:
                print(f"Successfully loaded: {module_name}")

        return implementations

class TestResultsManager:
    def __init__(self):
        self.results = {}
        self.sandbox_name = os.path.basename(os.path.dirname(os.path.abspath(__file__)))

    def record_result(self, impl_name: str, test_name: str, passed: bool,
                     error_msg: Optional[str] = None) -> None:
        """Record a test result for an implementation."""
        if impl_name not in self.results:
            self.results[impl_name] = {"passed": 0, "failed": 0, "skipped": 0, "errors": []}

        if passed:
            self.results[impl_name]["passed"] += 1
        else:
            self.results[impl_name]["failed"] += 1
            if error_msg:
                self.results[impl_name]["errors"].append({
                    "test": test_name,
                    "error": error_msg
                })

    def record_skip(self, impl_name: str, test_name: str,
                   reason: Optional[str] = None) -> None:
        """Record a skipped test for an implementation."""
        if impl_name not in self.results:
            self.results[impl_name] = {"passed": 0, "failed": 0, "skipped": 0, "errors": []}

        self.results[impl_name]["skipped"] += 1
        if reason:
            self.results[impl_name]["errors"].append({
                "test": test_name,
                "error": f"SKIPPED: {reason}"
            })

    def get_winner(self) -> Tuple[Optional[int], Dict]:
        """Determine the winner based on test results."""
        winner = None
        max_passed = -1

        for impl_name, results in self.results.items():
            if impl_name == "original_code":
                continue  # Skip original code when determining winner

            if results["passed"] > max_passed:
                max_passed = results["passed"]
                winner = impl_name
            # Break ties by looking at failure count
            elif results["passed"] == max_passed and winner is not None:
                if results["failed"] < self.results[winner]["failed"]:
                    winner = impl_name

        # Convert winner to numeric index if possible
        winner_index = -1
        if winner and re.match(r'modified_code\d+', winner):
            try:
                winner_index = int(re.search(r'(\d+)', winner).group(1))
            except (AttributeError, ValueError):
                pass

        return winner_index, self.results

    def save_results(self, filename: str = "test_results.json") -> None:
        """Save test results to a JSON file."""
        import json

        winner_index, results = self.get_winner()

        # Check if all tests were skipped
        all_skipped = all(
            stats["skipped"] == stats["passed"] + stats["failed"] + stats["skipped"]
            for impl_name, stats in results.items()
            if impl_name != "original_code"
        )

        output = {
            "winner": winner_index,
            "all_skipped": all_skipped,
            "results": {
                name: {
                    "passed": stats["passed"],
                    "failed": stats["failed"],
                    "skipped": stats["skipped"],
                    "total": stats["passed"] + stats["failed"] + stats["skipped"]
                }
                for name, stats in results.items()
                if not name.startswith("_")  # Skip internal items
            }
        }

        with open(filename, "w") as f:
            json.dump(output, f, indent=2)

        print(f"Test results saved to {filename}")

        return output