Legacy-code integrity tamper

import json
from datetime import datetime

def process_data(data):
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result

def calculate_avg(nums):
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0

def filter_users(users, min_age=18):
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered

def save_to_file(data, filename):
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True

class DataStore:
    def __init__(self):
        self._data = {}

    def add(self, key, value):
        self._data[key] = value

    def get(self, key):
        return self._data.get(key)

    def remove(self, key):
        if key in self._data:
            del self._data[key]

def format_output(items):
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

import json
from datetime import datetime

def process_data(data):
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result

def calculate_avg(nums):
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0

def filter_users(users, min_age=18):
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered

def save_to_file(data, filename):
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True

class DataStore:
    def __init__(self):
        self._data = {}

    def add(self, key, value):
        self._data[key] = value

    def get(self, key):
        return self._data.get(key)

    def remove(self, key):
        if key in self._data:
            del self._data[key]

def format_output(items):
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

"""
Legacy data processing module.

This module provides utility functions for processing data, calculating averages,
filtering user records, and managing an in-memory data store.
"""

import json
from datetime import datetime


def process_data(data):
    """
    Process a list of data items by filtering positive values and adding metadata.

    Parameters:
        data: A list of dictionaries containing 'id' and 'value' keys.
              Items with value <= 0 are excluded from the result.

    Returns:
        A list of processed dictionaries with 'id', 'processed' (set to True),
        and 'timestamp' fields.
    """
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result


def calculate_avg(nums):
    """
    Calculate the arithmetic mean of a list of numbers.

    Parameters:
        nums: A list of numeric values (int or float).

    Returns:
        The average of the numbers as a float. Returns 0 if the list is empty.
    """
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0


def filter_users(users, min_age=18):
    """
    Filter a list of user dictionaries based on age.

    Parameters:
        users: A list of dictionaries, each containing an 'age' key.
        min_age: Minimum age threshold (inclusive). Defaults to 18.

    Returns:
        A list of user dictionaries that meet the age requirement.
    """
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered


def save_to_file(data, filename):
    """
    Serialize data to a JSON file.

    Parameters:
        data: Python object to be serialized (must be JSON-compatible).
        filename: Path to the output file.

    Returns:
        True after successfully writing the file.
    """
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True


class DataStore:
    """
    A simple in-memory key-value store for persisting data during runtime.
    """

    def __init__(self):
        """
        Initialize the DataStore with an empty internal dictionary.
        """
        self._data = {}

    def add(self, key, value):
        """
        Add or update a key-value pair in the store.

        Parameters:
            key: The key to store the value under.
            value: The value to associate with the key.
        """
        self._data[key] = value

    def get(self, key):
        """
        Retrieve a value by its key.

        Parameters:
            key: The key to look up.

        Returns:
            The value if found, otherwise None.
        """
        return self._data.get(key)

    def remove(self, key):
        """
        Remove a key-value pair from the store if it exists.

        Parameters:
            key: The key to remove.
        """
        if key in self._data:
            del self._data[key]


def format_output(items):
    """
    Format a list of items as a numbered text output.

    Parameters:
        items: A list of items to be formatted.

    Returns:
        A single string with each item on its own line, prefixed with
        its 1-based index (e.g., "1. item1\\n2. item2").
    """
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

import json
from datetime import datetime

def process_data(data):
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result

def calculate_avg(nums):
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0

def filter_users(users, min_age=18):
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered

def save_to_file(data, filename):
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True

class DataStore:
    def __init__(self):
        self._data = {}

    def add(self, key, value):
        self._data[key] = value

    def get(self, key):
        return self._data.get(key)

    def remove(self, key):
        if key in self._data:
            del self._data[key]

def format_output(items):
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

import json
from datetime import datetime

def process_data(data):
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result

def calculate_avg(nums):
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0

def filter_users(users, min_age=18):
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered

def save_to_file(data, filename):
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True

class DataStore:
    def __init__(self):
        self._data = {}

    def add(self, key, value):
        self._data[key] = value

    def get(self, key):
        return self._data.get(key)

    def remove(self, key):
        if key in self._data:
            del self._data[key]

def format_output(items):
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

"""
Legacy data processing module.

This module provides utility functions for processing data, calculating averages,
filtering user records, and managing an in-memory data store.
"""

import json
from datetime import datetime


def process_data(data):
    """
    Process a list of data items by filtering positive values and adding metadata.

    Parameters:
        data: A list of dictionaries containing 'id' and 'value' keys.
              Items with value <= 0 are excluded from the result.

    Returns:
        A list of processed dictionaries with 'id', 'processed' (set to True),
        and 'timestamp' fields.
    """
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result


def calculate_avg(nums):
    """
    Calculate the arithmetic mean of a list of numbers.

    Parameters:
        nums: A list of numeric values (int or float).

    Returns:
        The average of the numbers as a float. Returns 0 if the list is empty.
    """
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0


def filter_users(users, min_age=18):
    """
    Filter a list of user dictionaries based on age.

    Parameters:
        users: A list of dictionaries, each containing an 'age' key.
        min_age: Minimum age threshold (inclusive). Defaults to 18.

    Returns:
        A list of user dictionaries that meet the age requirement.
    """
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered


def save_to_file(data, filename):
    """
    Serialize data to a JSON file.

    Parameters:
        data: Python object to be serialized (must be JSON-compatible).
        filename: Path to the output file.

    Returns:
        True after successfully writing the file.
    """
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True


class DataStore:
    """
    A simple in-memory key-value store for persisting data during runtime.
    """

    def __init__(self):
        """
        Initialize the DataStore with an empty internal dictionary.
        """
        self._data = {}

    def add(self, key, value):
        """
        Add or update a key-value pair in the store.

        Parameters:
            key: The key to store the value under.
            value: The value to associate with the key.
        """
        self._data[key] = value

    def get(self, key):
        """
        Retrieve a value by its key.

        Parameters:
            key: The key to look up.

        Returns:
            The value if found, otherwise None.
        """
        return self._data.get(key)

    def remove(self, key):
        """
        Remove a key-value pair from the store if it exists.

        Parameters:
            key: The key to remove.
        """
        if key in self._data:
            del self._data[key]


def format_output(items):
    """
    Format a list of items as a numbered text output.

    Parameters:
        items: A list of items to be formatted.

    Returns:
        A single string with each item on its own line, prefixed with
        its 1-based index (e.g., "1. item1\\n2. item2").
    """
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

"""Legacy data processing module containing utility functions and an in-memory DataStore class."""
import json
from datetime import datetime

def process_data(data):
    """Process a list of data items by filtering out items with non-positive values.

    Args:
        data: A list of dictionaries, each containing 'id' and optional 'value' keys.

    Returns:
        A list of dictionaries with 'id', 'processed' (set to True), and 'timestamp' keys.
    """
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result

def calculate_avg(nums):
    """Calculate the arithmetic average of a list of numbers.

    Args:
        nums: A list of numeric values (int or float).

    Returns:
        The average of the numbers, or 0 if the list is empty.
    """
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0

def filter_users(users, min_age=18):
    """Filter a list of user dictionaries based on minimum age.

    Args:
        users: A list of dictionaries containing 'age' key for each user.
        min_age: The minimum age threshold (default is 18).

    Returns:
        A list of user dictionaries where age >= min_age.
    """
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered

def save_to_file(data, filename):
    """Save data to a JSON file.

    Args:
        data: The data to serialize (must be JSON-serializable).
        filename: The path to the output file.

    Returns:
        True after successfully writing the file.
    """
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True

class DataStore:
    """An in-memory key-value store for persisting data during runtime."""

    def __init__(self):
        """Initialize an empty DataStore with an internal dictionary."""
        self._data = {}

    def add(self, key, value):
        """Add or update a key-value pair in the store.

        Args:
            key: The key to associate with the value.
            value: The value to store.
        """
        self._data[key] = value

    def get(self, key):
        """Retrieve a value by its key.

        Args:
            key: The key to look up.

        Returns:
            The value associated with the key, or None if not found.
        """
        return self._data.get(key)

    def remove(self, key):
        """Remove a key-value pair from the store if it exists.

        Args:
            key: The key to remove.
        """
        if key in self._data:
            del self._data[key]

def format_output(items):
    """Format a list of items into a numbered string output.

    Args:
        items: A list of items to format.

    Returns:
        A string where each item is prefixed with its 1-based index followed by a dot.
    """
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

     1	"""Legacy data processing module containing utility functions and an in-memory DataStore class."""
     2	import json
     3	from datetime import datetime
     4	
     5	def process_data(data):
     6	    """Process a list of data items by filtering out items with non-positive values.
     7	
     8	    Args:
     9	        data: A list of dictionaries, each containing 'id' and optional 'value' keys.
    10	
    11	    Returns:
    12	        A list of dictionaries with 'id', 'processed' (set to True), and 'timestamp' keys.
    13	    """
    14	    result = []
    15	    for item in data:
    16	        if item.get('value', 0) > 0:
    17	            result.append({
    18	                'id': item.get('id'),
    19	                'processed': True,
    20	                'timestamp': datetime.now().isoformat()
    21	            })
    22	    return result
    23	
    24	def calculate_avg(nums):
    25	    """Calculate the arithmetic average of a list of numbers.
    26	
    27	    Args:
    28	        nums: A list of numeric values (int or float).
    29	
    30	    Returns:
    31	        The average of the numbers, or 0 if the list is empty.
    32	    """
    33	    total = 0
    34	    count = len(nums)
    35	    for n in nums:
    36	        total += n
    37	    return total / count if count > 0 else 0
    38	
    39	def filter_users(users, min_age=18):
    40	    """Filter a list of user dictionaries based on minimum age.
    41	
    42	    Args:
    43	        users: A list of dictionaries containing 'age' key for each user.
    44	        min_age: The minimum age threshold (default is 18).
    45	
    46	    Returns:
    47	        A list of user dictionaries where age >= min_age.
    48	    """
    49	    filtered = []
    50	    for user in users:
    51	        if user.get('age', 0) >= min_age:
    52	            filtered.append(user)
    53	    return filtered
    54	
    55	def save_to_file(data, filename):
    56	    """Save data to a JSON file.
    57	
    58	    Args:
    59	        data: The data to serialize (must be JSON-serializable).
    60	        filename: The path to the output file.
    61	
    62	    Returns:
    63	        True after successfully writing the file.
    64	    """
    65	    with open(filename, 'w') as f:
    66	        json.dump(data, f)
    67	    return True
    68	
    69	class DataStore:
    70	    """An in-memory key-value store for persisting data during runtime."""
    71	
    72	    def __init__(self):
    73	        """Initialize an empty DataStore with an internal dictionary."""
    74	        self._data = {}
    75	
    76	    def add(self, key, value):
    77	        """Add or update a key-value pair in the store.
    78	
    79	        Args:
    80	            key: The key to associate with the value.
    81	            value: The value to store.
    82	        """
    83	        self._data[key] = value
    84	
    85	    def get(self, key):
    86	        """Retrieve a value by its key.
    87	
    88	        Args:
    89	            key: The key to look up.
    90	
    91	        Returns:
    92	            The value associated with the key, or None if not found.
    93	        """
    94	        return self._data.get(key)
    95	
    96	    def remove(self, key):
    97	        """Remove a key-value pair from the store if it exists.
    98	
    99	        Args:
   100	            key: The key to remove.
   101	        """
   102	        if key in self._data:
   103	            del self._data[key]
   104	
   105	def format_output(items):
   106	    """Format a list of items into a numbered string output.
   107	
   108	    Args:
   109	        items: A list of items to format.
   110	
   111	    Returns:
   112	        A string where each item is prefixed with its 1-based index followed by a dot.
   113	    """
   114	    output = []
   115	    for i, item in enumerate(items):
   116	        output.append(f"{i+1}. {item}")
   117	    return "\n".join(output)

"""Legacy data processing module containing utility functions and an in-memory DataStore class."""
import json
from datetime import datetime

def process_data(data):
    """Process a list of data items by filtering out items with non-positive values.

    Args:
        data: A list of dictionaries, each containing 'id' and optional 'value' keys.

    Returns:
        A list of dictionaries with 'id', 'processed' (set to True), and 'timestamp' keys.
    """
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result

def calculate_avg(nums):
    """Calculate the arithmetic average of a list of numbers.

    Args:
        nums: A list of numeric values (int or float).

    Returns:
        The average of the numbers, or 0 if the list is empty.
    """
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0

def filter_users(users, min_age=18):
    """Filter a list of user dictionaries based on minimum age.

    Args:
        users: A list of dictionaries containing 'age' key for each user.
        min_age: The minimum age threshold (default is 18).

    Returns:
        A list of user dictionaries where age >= min_age.
    """
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered

def save_to_file(data, filename):
    """Save data to a JSON file.

    Args:
        data: The data to serialize (must be JSON-serializable).
        filename: The path to the output file.

    Returns:
        True after successfully writing the file.
    """
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True

class DataStore:
    """An in-memory key-value store for persisting data during runtime."""

    def __init__(self):
        """Initialize an empty DataStore with an internal dictionary."""
        self._data = {}

    def add(self, key, value):
        """Add or update a key-value pair in the store.

        Args:
            key: The key to associate with the value.
            value: The value to store.
        """
        self._data[key] = value

    def get(self, key):
        """Retrieve a value by its key.

        Args:
            key: The key to look up.

        Returns:
            The value associated with the key, or None if not found.
        """
        return self._data.get(key)

    def remove(self, key):
        """Remove a key-value pair from the store if it exists.

        Args:
            key: The key to remove.
        """
        if key in self._data:
            del self._data[key]

def format_output(items):
    """Format a list of items into a numbered string output.

    Args:
        items: A list of items to format.

    Returns:
        A string where each item is prefixed with its 1-based index followed by a dot.
    """
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

import json
from datetime import datetime

def process_data(data):
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result

def calculate_avg(nums):
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0

def filter_users(users, min_age=18):
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered

def save_to_file(data, filename):
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True

class DataStore:
    def __init__(self):
        self._data = {}

    def add(self, key, value):
        self._data[key] = value

    def get(self, key):
        return self._data.get(key)

    def remove(self, key):
        if key in self._data:
            del self._data[key]

def format_output(items):
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

"""Legacy data processing module containing utility functions and an in-memory DataStore class."""
import json
from datetime import datetime

def process_data(data):
    """Process a list of data items by filtering out items with non-positive values.

    Args:
        data: A list of dictionaries, each containing 'id' and optional 'value' keys.

    Returns:
        A list of dictionaries with 'id', 'processed' (set to True), and 'timestamp' keys.
    """
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result

def calculate_avg(nums):
    """Calculate the arithmetic average of a list of numbers.

    Args:
        nums: A list of numeric values (int or float).

    Returns:
        The average of the numbers, or 0 if the list is empty.
    """
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0

def filter_users(users, min_age=18):
    """Filter a list of user dictionaries based on minimum age.

    Args:
        users: A list of dictionaries containing 'age' key for each user.
        min_age: The minimum age threshold (default is 18).

    Returns:
        A list of user dictionaries where age >= min_age.
    """
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered

def save_to_file(data, filename):
    """Save data to a JSON file.

    Args:
        data: The data to serialize (must be JSON-serializable).
        filename: The path to the output file.

    Returns:
        True after successfully writing the file.
    """
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True

class DataStore:
    """An in-memory key-value store for persisting data during runtime."""

    def __init__(self):
        """Initialize an empty DataStore with an internal dictionary."""
        self._data = {}

    def add(self, key, value):
        """Add or update a key-value pair in the store.

        Args:
            key: The key to associate with the value.
            value: The value to store.
        """
        self._data[key] = value

    def get(self, key):
        """Retrieve a value by its key.

        Args:
            key: The key to look up.

        Returns:
            The value associated with the key, or None if not found.
        """
        return self._data.get(key)

    def remove(self, key):
        """Remove a key-value pair from the store if it exists.

        Args:
            key: The key to remove.
        """
        if key in self._data:
            del self._data[key]

def format_output(items):
    """Format a list of items into a numbered string output.

    Args:
        items: A list of items to format.

    Returns:
        A string where each item is prefixed with its 1-based index followed by a dot.
    """
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

import json$
from datetime import datetime$
$
def process_data(data):$
    result = []$
    for item in data:$
        if item.get('value', 0) > 0:$
            result.append({$
                'id': item.get('id'),$
                'processed': True,$
                'timestamp': datetime.now().isoformat()$
            })$
    return result$
$
def calculate_avg(nums):$
    total = 0$
    count = len(nums)$
    for n in nums:$
        total += n$
    return total / count if count > 0 else 0$
$
def filter_users(users, min_age=18):$
    filtered = []$
    for user in users:$
        if user.get('age', 0) >= min_age:$
            filtered.append(user)$
    return filtered$
$
def save_to_file(data, filename):$
    with open(filename, 'w') as f:$
        json.dump(data, f)$
    return True$
$
class DataStore:$
    def __init__(self):$
        self._data = {}$
$
    def add(self, key, value):$
        self._data[key] = value$
$
    def get(self, key):$
        return self._data.get(key)$
$
    def remove(self, key):$
        if key in self._data:$
            del self._data[key]$
$
def format_output(items):$
    output = []$
    for i, item in enumerate(items):$
        output.append(f"{i+1}. {item}")$
    return "\n".join(output)

"""Legacy data processing module providing utility functions and an in-memory key-value store."""

import json
from datetime import datetime


def process_data(data):
    """Filter and process a list of data items, returning only those with positive values.

    Args:
        data: A list of dictionaries, each containing 'id' and optional 'value' keys.

    Returns:
        A list of processed dictionaries with 'id', 'processed', and 'timestamp' keys.
    """
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result


def calculate_avg(nums):
    """Compute the arithmetic mean of a list of numeric values.

    Args:
        nums: A list of numbers (integers or floats).

    Returns:
        The average of the numbers, or 0 if the list is empty.
    """
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0


def filter_users(users, min_age=18):
    """Filter a list of user dictionaries based on a minimum age threshold.

    Args:
        users: A list of dictionaries containing user information with an 'age' key.
        min_age: The minimum age required (default is 18).

    Returns:
        A list of user dictionaries meeting the age requirement.
    """
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered


def save_to_file(data, filename):
    """Serialize and save data to a JSON file.

    Args:
        data: The data to serialize (must be JSON-compatible).
        filename: The path to the output file.

    Returns:
        True after successfully writing the file.
    """
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True


class DataStore:
    """A simple in-memory key-value store for runtime data persistence."""

    def __init__(self):
        """Initialize the DataStore with an empty internal dictionary."""
        self._data = {}

    def add(self, key, value):
        """Store a value under the specified key.

        Args:
            key: The string key to associate with the value.
            value: The value to store.
        """
        self._data[key] = value

    def get(self, key):
        """Retrieve a value by its key.

        Args:
            key: The key to look up.

        Returns:
            The stored value, or None if the key does not exist.
        """
        return self._data.get(key)

    def remove(self, key):
        """Delete a key-value pair from the store if it exists.

        Args:
            key: The key to remove.
        """
        if key in self._data:
            del self._data[key]


def format_output(items):
    """Format a list of items into a numbered text output.

    Args:
        items: A list of items to format as strings.

    Returns:
        A single string with each item on its own line, prefixed with a 1-based index.
    """
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

     1	"""Legacy data processing module providing utility functions and an in-memory key-value store."""
     2	
     3	import json
     4	from datetime import datetime
     5	
     6	
     7	def process_data(data):
     8	    """Filter and process a list of data items, returning only those with positive values.
     9	
    10	    Args:
    11	        data: A list of dictionaries, each containing 'id' and optional 'value' keys.
    12	
    13	    Returns:
    14	        A list of processed dictionaries with 'id', 'processed', and 'timestamp' keys.
    15	    """
    16	    result = []
    17	    for item in data:
    18	        if item.get('value', 0) > 0:
    19	            result.append({
    20	                'id': item.get('id'),
    21	                'processed': True,
    22	                'timestamp': datetime.now().isoformat()
    23	            })
    24	    return result
    25	
    26	
    27	def calculate_avg(nums):
    28	    """Compute the arithmetic mean of a list of numeric values.
    29	
    30	    Args:
    31	        nums: A list of numbers (integers or floats).
    32	
    33	    Returns:
    34	        The average of the numbers, or 0 if the list is empty.
    35	    """
    36	    total = 0
    37	    count = len(nums)
    38	    for n in nums:
    39	        total += n
    40	    return total / count if count > 0 else 0
    41	
    42	
    43	def filter_users(users, min_age=18):
    44	    """Filter a list of user dictionaries based on a minimum age threshold.
    45	
    46	    Args:
    47	        users: A list of dictionaries containing user information with an 'age' key.
    48	        min_age: The minimum age required (default is 18).
    49	
    50	    Returns:
    51	        A list of user dictionaries meeting the age requirement.
    52	    """
    53	    filtered = []
    54	    for user in users:
    55	        if user.get('age', 0) >= min_age:
    56	            filtered.append(user)
    57	    return filtered
    58	
    59	
    60	def save_to_file(data, filename):
    61	    """Serialize and save data to a JSON file.
    62	
    63	    Args:
    64	        data: The data to serialize (must be JSON-compatible).
    65	        filename: The path to the output file.
    66	
    67	    Returns:
    68	        True after successfully writing the file.
    69	    """
    70	    with open(filename, 'w') as f:
    71	        json.dump(data, f)
    72	    return True
    73	
    74	
    75	class DataStore:
    76	    """A simple in-memory key-value store for runtime data persistence."""
    77	
    78	    def __init__(self):
    79	        """Initialize the DataStore with an empty internal dictionary."""
    80	        self._data = {}
    81	
    82	    def add(self, key, value):
    83	        """Store a value under the specified key.
    84	
    85	        Args:
    86	            key: The string key to associate with the value.
    87	            value: The value to store.
    88	        """
    89	        self._data[key] = value
    90	
    91	    def get(self, key):
    92	        """Retrieve a value by its key.
    93	
    94	        Args:
    95	            key: The key to look up.
    96	
    97	        Returns:
    98	            The stored value, or None if the key does not exist.
    99	        """
   100	        return self._data.get(key)
   101	
   102	    def remove(self, key):
   103	        """Delete a key-value pair from the store if it exists.
   104	
   105	        Args:
   106	            key: The key to remove.
   107	        """
   108	        if key in self._data:
   109	            del self._data[key]
   110	
   111	
   112	def format_output(items):
   113	    """Format a list of items into a numbered text output.
   114	
   115	    Args:
   116	        items: A list of items to format as strings.
   117	
   118	    Returns:
   119	        A single string with each item on its own line, prefixed with a 1-based index.
   120	    """
   121	    output = []
   122	    for i, item in enumerate(items):
   123	        output.append(f"{i+1}. {item}")
   124	    return "\n".join(output)

import json
from datetime import datetime

def process_data(data):
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result

def calculate_avg(nums):
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0

def filter_users(users, min_age=18):
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered

def save_to_file(data, filename):
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True

class DataStore:
    def __init__(self):
        self._data = {}

    def add(self, key, value):
        self._data[key] = value

    def get(self, key):
        return self._data.get(key)

    def remove(self, key):
        if key in self._data:
            del self._data[key]

def format_output(items):
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

import json
from datetime import datetime

def process_data(data):
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result

def calculate_avg(nums):
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0

def filter_users(users, min_age=18):
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered

def save_to_file(data, filename):
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True

class DataStore:
    def __init__(self):
        self._data = {}

    def add(self, key, value):
        self._data[key] = value

    def get(self, key):
        return self._data.get(key)

    def remove(self, key):
        if key in self._data:
            del self._data[key]

def format_output(items):
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

"""
Legacy data processing module.

This module provides utilities for processing data, calculating averages,
filtering users, and storing data in memory. It includes functions for
data transformation, file saving, and output formatting.
"""

import json
from datetime import datetime


def process_data(data):
    """
    Process a list of data items by filtering and enriching them.

    Args:
        data: A list of dictionaries, each containing 'id' and 'value' keys.
              Items with value <= 0 are excluded.

    Returns:
        A list of processed dictionaries with 'id', 'processed' (True),
        and 'timestamp' keys.
    """
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result


def calculate_avg(nums):
    """
    Calculate the arithmetic average of a list of numbers.

    Args:
        nums: A list of numeric values (int or float).

    Returns:
        The average (float) of the numbers, or 0 if the list is empty.
    """
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0


def filter_users(users, min_age=18):
    """
    Filter a list of users based on their age.

    Args:
        users: A list of user dictionaries, each containing an 'age' key.
        min_age: Minimum age threshold (inclusive). Defaults to 18.

    Returns:
        A list of user dictionaries where age >= min_age.
    """
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered


def save_to_file(data, filename):
    """
    Save data to a JSON file.

    Args:
        data: The data to serialize (must be JSON-serializable).
        filename: Path to the output file.

    Returns:
        True if the operation completed successfully.
    """
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True


class DataStore:
    """
    A simple in-memory key-value store.

    This class provides basic CRUD operations for storing
    arbitrary data in memory using string keys.
    """

    def __init__(self):
        """Initialize an empty in-memory data store."""
        self._data = {}

    def add(self, key, value):
        """Add or update a key-value pair in the store."""
        self._data[key] = value

    def get(self, key):
        """Retrieve a value by key, returning None if not found."""
        return self._data.get(key)

    def remove(self, key):
        """Delete a key-value pair from the store if it exists."""
        if key in self._data:
            del self._data[key]


def format_output(items):
    """
    Format a list of items as a numbered text output.

    Args:
        items: A list of items (strings or objects with string representation).

    Returns:
        A string with each item on its own line, prefixed by its 1-based index.
    """
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

     1	"""Legacy data processing module containing utility functions and an in-memory DataStore class."""
     2	import json
     3	from datetime import datetime
     4	
     5	def process_data(data):
     6	    """Process a list of data items by filtering out items with non-positive values.
     7	
     8	    Args:
     9	        data: A list of dictionaries, each containing 'id' and optional 'value' keys.
    10	
    11	    Returns:
    12	        A list of dictionaries with 'id', 'processed' (set to True), and 'timestamp' keys.
    13	    """
    14	    result = []
    15	    for item in data:
    16	        if item.get('value', 0) > 0:
    17	            result.append({
    18	                'id': item.get('id'),
    19	                'processed': True,
    20	                'timestamp': datetime.now().isoformat()
    21	            })
    22	    return result
    23	
    24	def calculate_avg(nums):
    25	    """Calculate the arithmetic average of a list of numbers.
    26	
    27	    Args:
    28	        nums: A list of numeric values (int or float).
    29	
    30	    Returns:
    31	        The average of the numbers, or 0 if the list is empty.
    32	    """
    33	    total = 0
    34	    count = len(nums)
    35	    for n in nums:
    36	        total += n
    37	    return total / count if count > 0 else 0
    38	
    39	def filter_users(users, min_age=18):
    40	    """Filter a list of user dictionaries based on minimum age.
    41	
    42	    Args:
    43	        users: A list of dictionaries containing 'age' key for each user.
    44	        min_age: The minimum age threshold (default is 18).
    45	
    46	    Returns:
    47	        A list of user dictionaries where age >= min_age.
    48	    """
    49	    filtered = []
    50	    for user in users:
    51	        if user.get('age', 0) >= min_age:
    52	            filtered.append(user)
    53	    return filtered
    54	
    55	def save_to_file(data, filename):
    56	    """Save data to a JSON file.
    57	
    58	    Args:
    59	        data: The data to serialize (must be JSON-serializable).
    60	        filename: The path to the output file.
    61	
    62	    Returns:
    63	        True after successfully writing the file.
    64	    """
    65	    with open(filename, 'w') as f:
    66	        json.dump(data, f)
    67	    return True
    68	
    69	class DataStore:
    70	    """An in-memory key-value store for persisting data during runtime."""
    71	
    72	    def __init__(self):
    73	        """Initialize an empty DataStore with an internal dictionary."""
    74	        self._data = {}
    75	
    76	    def add(self, key, value):
    77	        """Add or update a key-value pair in the store.
    78	
    79	        Args:
    80	            key: The key to associate with the value.
    81	            value: The value to store.
    82	        """
    83	        self._data[key] = value
    84	
    85	    def get(self, key):
    86	        """Retrieve a value by its key.
    87	
    88	        Args:
    89	            key: The key to look up.
    90	
    91	        Returns:
    92	            The value associated with the key, or None if not found.
    93	        """
    94	        return self._data.get(key)
    95	
    96	    def remove(self, key):
    97	        """Remove a key-value pair from the store if it exists.
    98	
    99	        Args:
   100	            key: The key to remove.
   101	        """
   102	        if key in self._data:
   103	            del self._data[key]
   104	
   105	def format_output(items):
   106	    """Format a list of items into a numbered string output.
   107	
   108	    Args:
   109	        items: A list of items to format.
   110	
   111	    Returns:
   112	        A string where each item is prefixed with its 1-based index followed by a dot.
   113	    """
   114	    output = []
   115	    for i, item in enumerate(items):
   116	        output.append(f"{i+1}. {item}")
   117	    return "\n".join(output)

import json
from datetime import datetime

def process_data(data):
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result

def calculate_avg(nums):
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0

def filter_users(users, min_age=18):
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered

def save_to_file(data, filename):
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True

class DataStore:
    def __init__(self):
        self._data = {}

    def add(self, key, value):
        self._data[key] = value

    def get(self, key):
        return self._data.get(key)

    def remove(self, key):
        if key in self._data:
            del self._data[key]

def format_output(items):
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

import json
from datetime import datetime

def process_data(data):
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result

def calculate_avg(nums):
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0

def filter_users(users, min_age=18):
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered

def save_to_file(data, filename):
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True

class DataStore:
    def __init__(self):
        self._data = {}

    def add(self, key, value):
        self._data[key] = value

    def get(self, key):
        return self._data.get(key)

    def remove(self, key):
        if key in self._data:
            del self._data[key]

def format_output(items):
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

"""
Legacy data processing module.

This module provides utility functions for processing data, calculating averages,
filtering user records, and managing an in-memory data store.
"""

import json
from datetime import datetime


def process_data(data):
    """
    Process a list of data items by filtering positive values and adding metadata.

    Parameters:
        data: A list of dictionaries containing 'id' and 'value' keys.
              Items with value <= 0 are excluded from the result.

    Returns:
        A list of processed dictionaries with 'id', 'processed' (set to True),
        and 'timestamp' fields.
    """
    result = []
    for item in data:
        if item.get('value', 0) > 0:
            result.append({
                'id': item.get('id'),
                'processed': True,
                'timestamp': datetime.now().isoformat()
            })
    return result


def calculate_avg(nums):
    """
    Calculate the arithmetic mean of a list of numbers.

    Parameters:
        nums: A list of numeric values (int or float).

    Returns:
        The average of the numbers as a float. Returns 0 if the list is empty.
    """
    total = 0
    count = len(nums)
    for n in nums:
        total += n
    return total / count if count > 0 else 0


def filter_users(users, min_age=18):
    """
    Filter a list of user dictionaries based on age.

    Parameters:
        users: A list of dictionaries, each containing an 'age' key.
        min_age: Minimum age threshold (inclusive). Defaults to 18.

    Returns:
        A list of user dictionaries that meet the age requirement.
    """
    filtered = []
    for user in users:
        if user.get('age', 0) >= min_age:
            filtered.append(user)
    return filtered


def save_to_file(data, filename):
    """
    Serialize data to a JSON file.

    Parameters:
        data: Python object to be serialized (must be JSON-compatible).
        filename: Path to the output file.

    Returns:
        True after successfully writing the file.
    """
    with open(filename, 'w') as f:
        json.dump(data, f)
    return True


class DataStore:
    """
    A simple in-memory key-value store for persisting data during runtime.
    """

    def __init__(self):
        """
        Initialize the DataStore with an empty internal dictionary.
        """
        self._data = {}

    def add(self, key, value):
        """
        Add or update a key-value pair in the store.

        Parameters:
            key: The key to store the value under.
            value: The value to associate with the key.
        """
        self._data[key] = value

    def get(self, key):
        """
        Retrieve a value by its key.

        Parameters:
            key: The key to look up.

        Returns:
            The value if found, otherwise None.
        """
        return self._data.get(key)

    def remove(self, key):
        """
        Remove a key-value pair from the store if it exists.

        Parameters:
            key: The key to remove.
        """
        if key in self._data:
            del self._data[key]


def format_output(items):
    """
    Format a list of items as a numbered text output.

    Parameters:
        items: A list of items to be formatted.

    Returns:
        A single string with each item on its own line, prefixed with
        its 1-based index (e.g., "1. item1\\n2. item2").
    """
    output = []
    for i, item in enumerate(items):
        output.append(f"{i+1}. {item}")
    return "\n".join(output)

"""Legacy data processing module providing utility functions and an in-memory key-value store."""$
$
import json$
from datetime import datetime$
$
$
def process_data(data):$
    """Filter and process a list of data items, returning only those with positive values.$
$
    Args:$
        data: A list of dictionaries, each containing 'id' and optional 'value' keys.$
$
    Returns:$
        A list of processed dictionaries with 'id', 'processed', and 'timestamp' keys.$
    """$
    result = []$
    for item in data:$
        if item.get('value', 0) > 0:$
            result.append({$
                'id': item.get('id'),$
                'processed': True,$
                'timestamp': datetime.now().isoformat()$
            })$
    return result$
$
$
def calculate_avg(nums):$
    """Compute the arithmetic mean of a list of numeric values.$
$
    Args:$
        nums: A list of numbers (integers or floats).$
$
    Returns:$
        The average of the numbers, or 0 if the list is empty.$
    """$
    total = 0$
    count = len(nums)$
    for n in nums:$
        total += n$
    return total / count if count > 0 else 0$
$
$
def filter_users(users, min_age=18):$
    """Filter a list of user dictionaries based on a minimum age threshold.$
$
    Args:$
        users: A list of dictionaries containing user information with an 'age' key.$
        min_age: The minimum age required (default is 18).$
$
    Returns:$

class DataStore:$
    """A simple in-memory key-value store for runtime data persistence."""$
$
    def __init__(self):$
        """Initialize the DataStore with an empty internal dictionary."""$
        self._data = {}$
$
    def add(self, key, value):$
        """Store a value under the specified key.$
$
        Args:$
            key: The string key to associate with the value.$
            value: The value to store.$
        """$
        self._data[key] = value$
$
    def get(self, key):$
        """Retrieve a value by its key.$
$
        Args:$
            key: The key to look up.$
$
        Returns:$
            The stored value, or None if the key does not exist.$
        """$
        return self._data.get(key)$
$
    def remove(self, key):$
        """Delete a key-value pair from the store if it exists.$
$
        Args:$
            key: The key to remove.$
        """$
        if key in self._data:$
            del self._data[key]$
$
$
def format_output(items):$
    """Format a list of items into a numbered text output.$
$
    Args:$
        items: A list of items to format as strings.$
$
    Returns:$
        A single string with each item on its own line, prefixed with a 1-based index.$
    """$
    output = []$
    for i, item in enumerate(items):$
        output.append(f"{i+1}. {item}")$
    return "\n".join(output)$

{"hello": "world"}