Format & Table Utilities

def split_format_str(fstr):
    """
    Split format string into components.
    
    Parameters:
    - fstr (str): Format string to split
    
    Returns:
    list: List of format string components
    """

def construct_format_field_str(fname, fspec, conv):
    """
    Build format field strings.
    
    Parameters:
    - fname (str): Field name
    - fspec (str): Format specification
    - conv (str): Conversion type
    
    Returns:
    str: Constructed format field string
    """

def infer_positional_format_args(fstr):
    """
    Infer positional argument count from format string.
    
    Parameters:
    - fstr (str): Format string to analyze
    
    Returns:
    int: Number of positional arguments required
    """

def get_format_args(fstr):
    """
    Extract all format arguments from format string.
    
    Parameters:
    - fstr (str): Format string to analyze
    
    Returns:
    list: List of format argument specifications
    """

def tokenize_format_str(fstr, resolve_pos=True):
    """
    Tokenize format string into components.
    
    Parameters:
    - fstr (str): Format string to tokenize
    - resolve_pos (bool): Resolve positional arguments
    
    Returns:
    list: List of format tokens
    """

class BaseFormatField:
    """Base class for format field representation."""
    def __init__(self, fname, fspec, conv): ...
    @property
    def field_name(self): ...
    @property
    def format_spec(self): ...
    @property
    def conversion(self): ...
    def __str__(self): ...

class DeferredValue:
    """Wrapper for values computed at format time."""
    def __init__(self, func, *args, **kwargs): ...
    def get_value(self): ...

class Table:
    """Flexible table data structure with multiple input/output formats."""
    def __init__(self, data=None, headers=None, **kwargs): ...
    
    # Properties
    @property
    def headers(self): ...
    @property  
    def data(self): ...
    @property
    def row_count(self): ...
    @property
    def col_count(self): ...
    
    # Data manipulation
    def add_row(self, row_data): ...
    def add_column(self, header, column_data): ...
    def extend(self, table_data): ...
    def sort(self, key=None, reverse=False): ...
    
    # Output formats
    def to_html(self, **kwargs): ...
    def to_text(self, **kwargs): ...
    def to_csv(self, **kwargs): ...
    def to_list(self): ...
    def to_dict(self): ...
    
    # Iteration
    def __iter__(self): ...
    def __getitem__(self, index): ...

class InputType:
    """Base class for table input type handlers."""
    def __init__(self, **kwargs): ...
    def normalize_data(self, data): ...

class DictInputType(InputType):
    """Handler for dictionary-based table data."""
    def normalize_data(self, data): ...

class ObjectInputType(InputType):
    """Handler for object-based table data."""
    def normalize_data(self, data): ...

class ListInputType(InputType):
    """Handler for list-based table data."""
    def normalize_data(self, data): ...

class TupleInputType(InputType):
    """Handler for tuple-based table data."""
    def normalize_data(self, data): ...

class NamedTupleInputType(InputType):
    """Handler for namedtuple-based table data."""
    def normalize_data(self, data): ...

def to_text(obj, maxlen=None):
    """
    Convert object to text representation.
    
    Parameters:
    - obj: Object to convert
    - maxlen (int, optional): Maximum length for text
    
    Returns:
    str: Text representation of object
    """

def escape_html(obj, maxlen=None):
    """
    HTML-escape object representation.
    
    Parameters:
    - obj: Object to escape
    - maxlen (int, optional): Maximum length before truncation
    
    Returns:
    str: HTML-escaped text representation
    """

from boltons.formatutils import get_format_args, split_format_str
from boltons.tableutils import Table, to_text

# Format string analysis
format_str = "Hello {name}, you have {count:d} {item}s!"
args = get_format_args(format_str)
print(args)  # Information about format arguments

components = split_format_str(format_str)
print(components)  # Format string broken into components

# Table creation from various data sources
# From list of dictionaries
dict_data = [
    {'name': 'Alice', 'age': 30, 'city': 'New York'},
    {'name': 'Bob', 'age': 25, 'city': 'Los Angeles'},
    {'name': 'Charlie', 'age': 35, 'city': 'Chicago'}
]

table = Table(dict_data)
print(table.to_text())

# HTML output
html_table = table.to_html(
    table_class='data-table',
    border=1,
    cellpadding=5
)
print(html_table)

# From list of lists with headers
list_data = [
    ['Alice', 30, 'New York'],
    ['Bob', 25, 'Los Angeles'],
    ['Charlie', 35, 'Chicago']
]
headers = ['Name', 'Age', 'City']

table2 = Table(list_data, headers=headers)
csv_output = table2.to_csv()
print(csv_output)

# From objects
class Person:
    def __init__(self, name, age, city):
        self.name = name
        self.age = age
        self.city = city

people = [
    Person('Alice', 30, 'New York'),
    Person('Bob', 25, 'Los Angeles'),
    Person('Charlie', 35, 'Chicago')
]

table3 = Table(people)
print(table3.to_text(max_col_width=15))

from boltons.tableutils import Table

# Create table and manipulate data
sales_data = [
    {'product': 'Widget', 'quantity': 100, 'price': 10.50},
    {'product': 'Gadget', 'quantity': 75, 'price': 25.00},
    {'product': 'Doohickey', 'quantity': 50, 'price': 15.75}
]

table = Table(sales_data)

# Add calculated column
revenue_data = [row['quantity'] * row['price'] for row in sales_data]
table.add_column('Revenue', revenue_data)

# Sort by revenue (descending)
table.sort(key=lambda row: row[-1], reverse=True)  # Sort by last column (Revenue)

# Add totals row
total_qty = sum(row[1] for row in table.data)
total_revenue = sum(row[3] for row in table.data)
table.add_row(['TOTAL', total_qty, '', total_revenue])

# Generate formatted output
print("Sales Report:")
print("=" * 60)
print(table.to_text(max_col_width=12))

# Custom HTML formatting
html_output = table.to_html(
    table_class='sales-report',
    table_style='border-collapse: collapse; width: 100%;',
    th_style='background-color: #f2f2f2; padding: 8px;',
    td_style='padding: 8px; border-bottom: 1px solid #ddd;'
)

# Export to various formats
with open('sales_report.csv', 'w') as f:
    f.write(table.to_csv())

# Iterate through table data
print("Individual rows:")
for i, row in enumerate(table):
    print(f"Row {i}: {row}")

# Access specific cells
print(f"Product in first row: {table[0][0]}")
print(f"Revenue in second row: {table[1][3]}")

from boltons.formatutils import (
    tokenize_format_str, infer_positional_format_args, 
    BaseFormatField, DeferredValue
)

# Analyze complex format strings
complex_format = "Item: {item.name:>20}, Price: ${item.price:8.2f}, Stock: {stock:d}"

# Tokenize the format string
tokens = tokenize_format_str(complex_format)
print("Format tokens:")
for token in tokens:
    print(f"  {token}")

# Infer argument requirements
pos_args_needed = infer_positional_format_args("{0} + {1} = {2}")
print(f"Positional arguments needed: {pos_args_needed}")  # 3

# Dynamic value formatting with DeferredValue
import datetime

def current_time():
    return datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")

deferred_time = DeferredValue(current_time)

# Format string with deferred evaluation
log_format = "Log entry at {timestamp}: {message}"
formatted = log_format.format(
    timestamp=deferred_time.get_value(),
    message="System started"
)
print(formatted)

# Exceptions
class UnsupportedData(TypeError):
    """Exception for unsupported data types in table processing."""
    pass

# Format field components
FormatToken = tuple  # (literal_text, field_spec) pairs from tokenized format strings