🔗 Function Composition in TuskLang - Ruby Edition

"We don't bow to any king" - Ruby Edition

TuskLang's function composition provides powerful functional programming capabilities that integrate seamlessly with Ruby's rich functional features, enabling dynamic function chaining, transformation pipelines, and intelligent data processing workflows.

🎯 Overview

Function composition in TuskLang allows you to combine multiple functions into powerful transformation pipelines, enabling complex data processing, validation chains, and business logic workflows. When combined with Ruby's functional programming capabilities, these operations become incredibly versatile.

🚀 Basic Function Composition

Simple Function Chaining

TuskLang configuration with function composition
tsk_content = <<~TSK
  [function_composition]
  # Basic function chaining
  processed_user: @pipe(@env("USER_INPUT"), [
    @trim,
    @lower,
    @replace("  ", " ")
  ])
  
  # Data transformation pipeline
  user_data_pipeline: @pipe(@query("SELECT name, email FROM users WHERE id = ?", @env("USER_ID")), [
    @validate_user_data,
    @sanitize_user_data,
    @format_user_data
  ])
  
  # Configuration processing
  config_pipeline: @pipe(@env("RAW_CONFIG"), [
    @parse_json,
    @validate_config_schema,
    @apply_defaults,
    @encrypt_sensitive_data
  ])
TSK
Ruby integration
require 'tusklang'
parser = TuskLang.new
config = parser.parse(tsk_content)
Use in Ruby classes
class FunctionComposer
  def initialize(tusk_config)
    @config = tusk_config
  end
  
  def get_processed_user
    @config['function_composition']['processed_user']
  end
  
  def get_user_data_pipeline
    @config['function_composition']['user_data_pipeline']
  end
  
  def get_config_pipeline
    @config['function_composition']['config_pipeline']
  end
  
  def process_user_input(input)
    # Simulate the TuskLang pipeline in Ruby
    input.to_s.strip.downcase.gsub(/\s+/, ' ')
  end
  
  def process_user_data(user_data)
    # Simulate the user data pipeline
    validated = validate_user_data(user_data)
    sanitized = sanitize_user_data(validated)
    format_user_data(sanitized)
  end
  
  private
  
  def validate_user_data(data)
    # Validation logic
    data
  end
  
  def sanitize_user_data(data)
    # Sanitization logic
    data
  end
  
  def format_user_data(data)
    # Formatting logic
    data
  end
end
Usage
composer = FunctionComposer.new(config)
puts composer.process_user_input("  JOHN DOE  ")

Conditional Function Composition

TuskLang with conditional composition
tsk_content = <<~TSK
  [conditional_composition]
  # Conditional function chains
  conditional_user_processing: @when(@env("IS_ADMIN") == "true", 
    @pipe(@env("USER_INPUT"), [@validate_admin, @process_admin, @log_admin_action]),
    @pipe(@env("USER_INPUT"), [@validate_user, @process_user, @log_user_action])
  )
  
  # Environment-specific pipelines
  production_pipeline: @when(@env("RAILS_ENV") == "production",
    @pipe(@data, [@validate, @sanitize, @encrypt, @log]),
    @pipe(@data, [@validate, @log])
  )
  
  # Feature flag based composition
  feature_enabled_pipeline: @when(@env("NEW_FEATURE_ENABLED") == "true",
    @pipe(@user_data, [@legacy_validation, @new_validation, @enhanced_processing]),
    @pipe(@user_data, [@legacy_validation, @legacy_processing])
  )
TSK
Ruby integration with conditional composition
class ConditionalComposer
  def initialize(tusk_config)
    @config = tusk_config
  end
  
  def get_conditional_user_processing
    @config['conditional_composition']['conditional_user_processing']
  end
  
  def get_production_pipeline
    @config['conditional_composition']['production_pipeline']
  end
  
  def get_feature_enabled_pipeline
    @config['conditional_composition']['feature_enabled_pipeline']
  end
  
  def process_user_conditionally(user_input, is_admin)
    if is_admin
      pipe(user_input, [:validate_admin, :process_admin, :log_admin_action])
    else
      pipe(user_input, [:validate_user, :process_user, :log_user_action])
    end
  end
  
  def process_data_for_environment(data, environment)
    if environment == 'production'
      pipe(data, [:validate, :sanitize, :encrypt, :log])
    else
      pipe(data, [:validate, :log])
    end
  end
  
  private
  
  def pipe(data, functions)
    functions.reduce(data) { |result, func| send(func, result) }
  end
  
  def validate_admin(data)
    # Admin validation logic
    data
  end
  
  def process_admin(data)
    # Admin processing logic
    data
  end
  
  def log_admin_action(data)
    # Admin logging logic
    data
  end
  
  def validate_user(data)
    # User validation logic
    data
  end
  
  def process_user(data)
    # User processing logic
    data
  end
  
  def log_user_action(data)
    # User logging logic
    data
  end
end

🔧 Advanced Function Composition

Complex Transformation Pipelines

TuskLang with complex pipelines
tsk_content = <<~TSK
  [complex_pipelines]
  # Multi-stage data processing
  data_processing_pipeline: @pipe(@raw_data, [
    @parse_input,
    @validate_schema,
    @transform_data,
    @apply_business_rules,
    @sanitize_output,
    @format_response
  ])
  
  # Error handling pipeline
  error_safe_pipeline: @try_catch(@pipe(@user_input, [
    @parse_json,
    @validate_data,
    @process_data
  ]), @handle_error)
  
  # Parallel processing pipeline
  parallel_pipeline: @parallel([
    @pipe(@user_data, [@validate, @process]),
    @pipe(@user_data, [@analyze, @report]),
    @pipe(@user_data, [@audit, @log])
  ])
TSK
Ruby integration with complex pipelines
class ComplexPipelineProcessor
  def initialize(tusk_config)
    @config = tusk_config
  end
  
  def get_data_processing_pipeline
    @config['complex_pipelines']['data_processing_pipeline']
  end
  
  def get_error_safe_pipeline
    @config['complex_pipelines']['error_safe_pipeline']
  end
  
  def get_parallel_pipeline
    @config['complex_pipelines']['parallel_pipeline']
  end
  
  def process_data_pipeline(raw_data)
    pipe(raw_data, [
      :parse_input,
      :validate_schema,
      :transform_data,
      :apply_business_rules,
      :sanitize_output,
      :format_response
    ])
  end
  
  def process_with_error_handling(user_input)
    begin
      pipe(user_input, [:parse_json, :validate_data, :process_data])
    rescue => e
      handle_error(e)
    end
  end
  
  def process_in_parallel(user_data)
    results = []
    
    # Simulate parallel processing
    threads = [
      Thread.new { results << pipe(user_data, [:validate, :process]) },
      Thread.new { results << pipe(user_data, [:analyze, :report]) },
      Thread.new { results << pipe(user_data, [:audit, :log]) }
    ]
    
    threads.each(&:join)
    results
  end
  
  private
  
  def pipe(data, functions)
    functions.reduce(data) { |result, func| send(func, result) }
  end
  
  def parse_input(data)
    # Parse input logic
    data
  end
  
  def validate_schema(data)
    # Schema validation logic
    data
  end
  
  def transform_data(data)
    # Data transformation logic
    data
  end
  
  def apply_business_rules(data)
    # Business rules logic
    data
  end
  
  def sanitize_output(data)
    # Output sanitization logic
    data
  end
  
  def format_response(data)
    # Response formatting logic
    data
  end
  
  def handle_error(error)
    Rails.logger.error "Pipeline error: #{error.message}"
    { error: error.message, status: 'failed' }
  end
end

Function Composition with State

TuskLang with stateful composition
tsk_content = <<~TSK
  [stateful_composition]
  # Stateful function composition
  stateful_pipeline: @with_state(@initial_state, @pipe(@data, [
    @update_state("step1"),
    @process_data,
    @update_state("step2"),
    @validate_result,
    @update_state("complete")
  ]))
  
  # Accumulator pattern
  accumulator_pipeline: @reduce(@data_array, @initial_value, [
    @accumulate_data,
    @transform_accumulated,
    @validate_accumulated
  ])
  
  # Context-aware composition
  context_pipeline: @with_context(@create_context, @pipe(@user_data, [
    @set_user_context,
    @process_with_context,
    @log_with_context,
    @clear_context
  ]))
TSK
Ruby integration with stateful composition
class StatefulComposer
  def initialize(tusk_config)
    @config = tusk_config
  end
  
  def get_stateful_pipeline
    @config['stateful_composition']['stateful_pipeline']
  end
  
  def get_accumulator_pipeline
    @config['stateful_composition']['accumulator_pipeline']
  end
  
  def get_context_pipeline
    @config['stateful_composition']['context_pipeline']
  end
  
  def process_with_state(data, initial_state)
    state = initial_state.dup
    
    pipe_with_state(data, state, [
      ->(data, state) { [data, update_state(state, "step1")] },
      ->(data, state) { [process_data(data), state] },
      ->(data, state) { [data, update_state(state, "step2")] },
      ->(data, state) { [validate_result(data), state] },
      ->(data, state) { [data, update_state(state, "complete")] }
    ])
  end
  
  def process_with_accumulator(data_array, initial_value)
    data_array.reduce(initial_value) do |accumulator, data|
      accumulated = accumulate_data(accumulator, data)
      transformed = transform_accumulated(accumulated)
      validate_accumulated(transformed)
    end
  end
  
  def process_with_context(user_data)
    context = create_context
    
    pipe_with_context(user_data, context, [
      ->(data, context) { [data, set_user_context(context, data)] },
      ->(data, context) { [process_with_context(data, context), context] },
      ->(data, context) { [data, log_with_context(context, data)] },
      ->(data, context) { [data, clear_context(context)] }
    ])
  end
  
  private
  
  def pipe_with_state(data, state, functions)
    functions.reduce([data, state]) { |(data, state), func| func.call(data, state) }
  end
  
  def pipe_with_context(data, context, functions)
    functions.reduce([data, context]) { |(data, context), func| func.call(data, context) }
  end
  
  def update_state(state, step)
    state.merge({ current_step: step, updated_at: Time.current })
  end
  
  def process_data(data)
    # Process data logic
    data
  end
  
  def validate_result(data)
    # Validation logic
    data
  end
  
  def accumulate_data(accumulator, data)
    # Accumulation logic
    accumulator + data
  end
  
  def transform_accumulated(accumulated)
    # Transformation logic
    accumulated
  end
  
  def validate_accumulated(transformed)
    # Validation logic
    transformed
  end
  
  def create_context
    { session_id: SecureRandom.uuid, created_at: Time.current }
  end
  
  def set_user_context(context, user_data)
    context.merge({ user_id: user_data[:id] })
  end
  
  def process_with_context(data, context)
    # Context-aware processing
    data
  end
  
  def log_with_context(context, data)
    Rails.logger.info "Processing with context: #{context}"
    context
  end
  
  def clear_context(context)
    context.merge({ cleared_at: Time.current })
  end
end

🎛️ Higher-Order Functions

Function Factories and Currying

TuskLang with higher-order functions
tsk_content = <<~TSK
  [higher_order_functions]
  # Function factory
  create_validator: @factory(@validation_rules, @create_validation_function)
  
  # Curried functions
  curried_processor: @curry(@process_data, @env("PROCESSING_MODE"))
  curried_validator: @curry(@validate_data, @env("VALIDATION_LEVEL"))
  
  # Partial application
  partial_processor: @partial(@process_user_data, @env("USER_ROLE"))
  partial_logger: @partial(@log_action, @env("LOG_LEVEL"))
  
  # Function composition with curried functions
  composed_processor: @compose(@curried_processor, @curried_validator, @partial_logger)
TSK
Ruby integration with higher-order functions
class HigherOrderFunctionProcessor
  def initialize(tusk_config)
    @config = tusk_config
  end
  
  def get_create_validator
    @config['higher_order_functions']['create_validator']
  end
  
  def get_curried_processor
    @config['higher_order_functions']['curried_processor']
  end
  
  def get_composed_processor
    @config['higher_order_functions']['composed_processor']
  end
  
  def create_validator_factory(validation_rules)
    ->(data) { validate_with_rules(data, validation_rules) }
  end
  
  def curry_processor(processing_mode)
    ->(data) { process_data(data, processing_mode) }
  end
  
  def curry_validator(validation_level)
    ->(data) { validate_data(data, validation_level) }
  end
  
  def partial_processor(user_role)
    ->(data) { process_user_data(data, user_role) }
  end
  
  def compose_processors(*functions)
    ->(data) { functions.reduce(data) { |result, func| func.call(result) } }
  end
  
  def process_with_composition(data)
    processor = curry_processor(ENV['PROCESSING_MODE'])
    validator = curry_validator(ENV['VALIDATION_LEVEL'])
    logger = partial_processor(ENV['USER_ROLE'])
    
    composed = compose_processors(processor, validator, logger)
    composed.call(data)
  end
  
  private
  
  def validate_with_rules(data, rules)
    # Validation logic with rules
    data
  end
  
  def process_data(data, mode)
    # Processing logic with mode
    data
  end
  
  def validate_data(data, level)
    # Validation logic with level
    data
  end
  
  def process_user_data(data, role)
    # User processing logic with role
    data
  end
end

Monadic Function Composition

TuskLang with monadic composition
tsk_content = <<~TSK
  [monadic_composition]
  # Maybe monad composition
  maybe_pipeline: @maybe(@user_data, [
    @parse_user_data,
    @validate_user_data,
    @process_user_data,
    @format_user_data
  ])
  
  # Either monad composition
  either_pipeline: @either(@user_input, [
    @parse_input,
    @validate_input,
    @process_input
  ], @handle_error)
  
  # Result monad composition
  result_pipeline: @result(@data_operation, [
    @validate_result,
    @transform_result,
    @format_result
  ])
TSK
Ruby integration with monadic composition
class MonadicComposer
  def initialize(tusk_config)
    @config = tusk_config
  end
  
  def get_maybe_pipeline
    @config['monadic_composition']['maybe_pipeline']
  end
  
  def get_either_pipeline
    @config['monadic_composition']['either_pipeline']
  end
  
  def get_result_pipeline
    @config['monadic_composition']['result_pipeline']
  end
  
  def process_maybe_pipeline(user_data)
    return nil if user_data.nil?
    
    result = user_data
    result = parse_user_data(result) if result
    result = validate_user_data(result) if result
    result = process_user_data(result) if result
    result = format_user_data(result) if result
    
    result
  end
  
  def process_either_pipeline(user_input)
    begin
      result = user_input
      result = parse_input(result)
      result = validate_input(result)
      result = process_input(result)
      { success: true, data: result }
    rescue => e
      { success: false, error: handle_error(e) }
    end
  end
  
  def process_result_pipeline(data_operation)
    result = data_operation
    return { success: false, error: result } if result.is_a?(Exception)
    
    result = validate_result(result)
    result = transform_result(result)
    result = format_result(result)
    
    { success: true, data: result }
  end
  
  private
  
  def parse_user_data(data)
    # Parse logic
    data
  end
  
  def validate_user_data(data)
    # Validation logic
    data
  end
  
  def process_user_data(data)
    # Processing logic
    data
  end
  
  def format_user_data(data)
    # Formatting logic
    data
  end
  
  def parse_input(input)
    # Parse logic
    input
  end
  
  def validate_input(input)
    # Validation logic
    input
  end
  
  def process_input(input)
    # Processing logic
    input
  end
  
  def handle_error(error)
    Rails.logger.error "Pipeline error: #{error.message}"
    error.message
  end
  
  def validate_result(result)
    # Result validation logic
    result
  end
  
  def transform_result(result)
    # Result transformation logic
    result
  end
  
  def format_result(result)
    # Result formatting logic
    result
  end
end

🔄 Dynamic Function Composition

Runtime Function Composition

TuskLang with runtime composition
tsk_content = <<~TSK
  [runtime_composition]
  # Dynamic function selection
  dynamic_pipeline: @compose_dynamic(@user_data, @get_pipeline_config(@env("PIPELINE_TYPE")))
  
  # Plugin-based composition
  plugin_pipeline: @compose_plugins(@user_data, @get_enabled_plugins())
  
  # Configuration-driven composition
  config_pipeline: @compose_from_config(@user_data, @load_pipeline_config(@env("CONFIG_PATH")))
  
  # A/B testing composition
  ab_test_pipeline: @ab_test_compose(@user_data, @get_experiment_config(@env("EXPERIMENT_ID")))
TSK
Ruby integration with runtime composition
class RuntimeComposer
  def initialize(tusk_config)
    @config = tusk_config
  end
  
  def get_dynamic_pipeline
    @config['runtime_composition']['dynamic_pipeline']
  end
  
  def get_plugin_pipeline
    @config['runtime_composition']['plugin_pipeline']
  end
  
  def get_config_pipeline
    @config['runtime_composition']['config_pipeline']
  end
  
  def get_ab_test_pipeline
    @config['runtime_composition']['ab_test_pipeline']
  end
  
  def process_dynamic_pipeline(user_data, pipeline_type)
    pipeline_config = get_pipeline_config(pipeline_type)
    compose_and_execute(user_data, pipeline_config)
  end
  
  def process_plugin_pipeline(user_data)
    enabled_plugins = get_enabled_plugins
    compose_and_execute(user_data, enabled_plugins)
  end
  
  def process_config_pipeline(user_data, config_path)
    pipeline_config = load_pipeline_config(config_path)
    compose_and_execute(user_data, pipeline_config)
  end
  
  def process_ab_test_pipeline(user_data, experiment_id)
    experiment_config = get_experiment_config(experiment_id)
    variant = select_variant(experiment_config)
    compose_and_execute(user_data, variant)
  end
  
  private
  
  def compose_and_execute(data, functions)
    functions.reduce(data) { |result, func| send(func, result) }
  end
  
  def get_pipeline_config(type)
    case type
    when 'simple'
      [:validate, :process, :format]
    when 'complex'
      [:validate, :sanitize, :process, :transform, :format]
    else
      [:validate, :process]
    end
  end
  
  def get_enabled_plugins
    # Get enabled plugins from configuration
    [:plugin_validate, :plugin_process, :plugin_log]
  end
  
  def load_pipeline_config(path)
    # Load pipeline configuration from file
    [:load_validate, :load_process, :load_format]
  end
  
  def get_experiment_config(experiment_id)
    # Get A/B test configuration
    {
      variant_a: [:validate_a, :process_a],
      variant_b: [:validate_b, :process_b]
    }
  end
  
  def select_variant(config)
    # Select A/B test variant
    rand < 0.5 ? config[:variant_a] : config[:variant_b]
  end
end

🛡️ Error Handling and Validation

Function Composition Error Handling

TuskLang with error handling
tsk_content = <<~TSK
  [error_handling]
  # Error handling in composition
  safe_pipeline: @try_catch(@pipe(@user_data, [
    @parse_data,
    @validate_data,
    @process_data
  ]), @handle_pipeline_error)
  
  # Retry logic in composition
  retry_pipeline: @retry(@pipe(@api_call, [
    @validate_response,
    @process_response
  ]), 3, @exponential_backoff)
  
  # Circuit breaker pattern
  circuit_breaker_pipeline: @circuit_breaker(@pipe(@external_service, [
    @call_service,
    @process_result
  ]), @handle_service_failure)
TSK
Ruby integration with error handling
class ErrorHandlingComposer
  def initialize(tusk_config)
    @config = tusk_config
  end
  
  def get_safe_pipeline
    @config['error_handling']['safe_pipeline']
  end
  
  def get_retry_pipeline
    @config['error_handling']['retry_pipeline']
  end
  
  def get_circuit_breaker_pipeline
    @config['error_handling']['circuit_breaker_pipeline']
  end
  
  def process_safe_pipeline(user_data)
    begin
      pipe(user_data, [:parse_data, :validate_data, :process_data])
    rescue => e
      handle_pipeline_error(e)
    end
  end
  
  def process_retry_pipeline(api_call)
    retries = 0
    max_retries = 3
    
    begin
      pipe(api_call, [:validate_response, :process_response])
    rescue => e
      retries += 1
      if retries <= max_retries
        sleep(exponential_backoff(retries))
        retry
      else
        raise e
      end
    end
  end
  
  def process_circuit_breaker_pipeline(external_service)
    if circuit_open?
      handle_service_failure("Circuit breaker is open")
    else
      begin
        result = pipe(external_service, [:call_service, :process_result])
        reset_circuit
        result
      rescue => e
        record_failure
        handle_service_failure(e)
      end
    end
  end
  
  private
  
  def pipe(data, functions)
    functions.reduce(data) { |result, func| send(func, result) }
  end
  
  def parse_data(data)
    # Parse logic
    data
  end
  
  def validate_data(data)
    # Validation logic
    data
  end
  
  def process_data(data)
    # Processing logic
    data
  end
  
  def handle_pipeline_error(error)
    Rails.logger.error "Pipeline error: #{error.message}"
    { error: error.message, status: 'failed' }
  end
  
  def validate_response(response)
    # Response validation logic
    response
  end
  
  def process_response(response)
    # Response processing logic
    response
  end
  
  def exponential_backoff(retry_count)
    2 ** retry_count
  end
  
  def call_service(service)
    # Service call logic
    service
  end
  
  def process_result(result)
    # Result processing logic
    result
  end
  
  def handle_service_failure(error)
    Rails.logger.error "Service failure: #{error}"
    { error: error.to_s, status: 'service_failed' }
  end
  
  def circuit_open?
    # Circuit breaker logic
    false
  end
  
  def record_failure
    # Record failure logic
  end
  
  def reset_circuit
    # Reset circuit logic
  end
end

🚀 Performance Optimization

Efficient Function Composition

TuskLang with performance optimizations
tsk_content = <<~TSK
  [optimized_composition]
  # Cached function composition
  cached_pipeline: @cache("5m", @pipe(@user_data, [
    @expensive_validation,
    @expensive_processing,
    @expensive_formatting
  ]))
  
  # Lazy evaluation in composition
  lazy_pipeline: @lazy(@pipe(@user_data, [
    @expensive_operation,
    @another_expensive_operation
  ]))
  
  # Parallel function composition
  parallel_pipeline: @parallel_compose(@user_data, [
    @independent_operation_1,
    @independent_operation_2,
    @independent_operation_3
  ])
  
  # Streaming composition
  stream_pipeline: @stream_compose(@large_dataset, [
    @process_chunk,
    @validate_chunk,
    @format_chunk
  ])
TSK
Ruby integration with optimized composition
class OptimizedComposer
  def initialize(tusk_config)
    @config = tusk_config
  end
  
  def get_cached_pipeline
    @config['optimized_composition']['cached_pipeline']
  end
  
  def get_lazy_pipeline
    @config['optimized_composition']['lazy_pipeline']
  end
  
  def get_parallel_pipeline
    @config['optimized_composition']['parallel_pipeline']
  end
  
  def get_stream_pipeline
    @config['optimized_composition']['stream_pipeline']
  end
  
  def process_cached_pipeline(user_data)
    Rails.cache.fetch("pipeline_#{user_data.hash}", expires_in: 5.minutes) do
      pipe(user_data, [:expensive_validation, :expensive_processing, :expensive_formatting])
    end
  end
  
  def process_lazy_pipeline(user_data)
    # Lazy evaluation using Ruby's Enumerator
    Enumerator.new do |yielder|
      result = user_data
      result = expensive_operation(result)
      yielder << result
      result = another_expensive_operation(result)
      yielder << result
    end
  end
  
  def process_parallel_pipeline(user_data)
    threads = [
      Thread.new { independent_operation_1(user_data) },
      Thread.new { independent_operation_2(user_data) },
      Thread.new { independent_operation_3(user_data) }
    ]
    
    threads.map(&:value)
  end
  
  def process_stream_pipeline(large_dataset)
    large_dataset.each_slice(1000) do |chunk|
      result = pipe(chunk, [:process_chunk, :validate_chunk, :format_chunk])
      yield result if block_given?
    end
  end
  
  private
  
  def pipe(data, functions)
    functions.reduce(data) { |result, func| send(func, result) }
  end
  
  def expensive_validation(data)
    # Expensive validation logic
    sleep(0.1) # Simulate expensive operation
    data
  end
  
  def expensive_processing(data)
    # Expensive processing logic
    sleep(0.1) # Simulate expensive operation
    data
  end
  
  def expensive_formatting(data)
    # Expensive formatting logic
    sleep(0.1) # Simulate expensive operation
    data
  end
  
  def expensive_operation(data)
    # Expensive operation logic
    data
  end
  
  def another_expensive_operation(data)
    # Another expensive operation logic
    data
  end
  
  def independent_operation_1(data)
    # Independent operation 1
    data
  end
  
  def independent_operation_2(data)
    # Independent operation 2
    data
  end
  
  def independent_operation_3(data)
    # Independent operation 3
    data
  end
  
  def process_chunk(chunk)
    # Process chunk logic
    chunk
  end
  
  def validate_chunk(chunk)
    # Validate chunk logic
    chunk
  end
  
  def format_chunk(chunk)
    # Format chunk logic
    chunk
  end
end

🎯 Best Practices

1. Use Descriptive Function Names

Good
user_processing_pipeline: @pipe(@user_data, [@validate_user_input, @process_user_data, @format_user_response])
data_transformation_chain: @compose(@parse_data, @validate_data, @transform_data)
Avoid
pipeline: @pipe(@data, [@func1, @func2, @func3])
chain: @compose(@f1, @f2, @f3)

2. Handle Errors Gracefully

TuskLang with error handling
tsk_content = <<~TSK
  [error_handling_best_practices]
  # Always wrap pipelines in error handling
  safe_pipeline: @try_catch(@pipe(@data, [@step1, @step2, @step3]), @handle_error)
  
  # Use appropriate error handling for different scenarios
  retry_pipeline: @retry(@pipe(@api_call, [@validate, @process]), 3, @backoff)
TSK

3. Use Caching for Expensive Operations

Cache expensive function compositions
expensive_pipeline: @cache("10m", @pipe(@data, [@expensive_step1, @expensive_step2]))

4. Keep Functions Pure When Possible

TuskLang with pure functions
tsk_content = <<~TSK
  [pure_functions]
  # Pure function composition
  pure_pipeline: @pipe(@input_data, [
    @pure_transform,
    @pure_validate,
    @pure_format
  ])
  
  # Side effects isolated
  side_effect_pipeline: @pipe(@data, [
    @pure_process,
    @side_effect_log,
    @pure_format
  ])
TSK

🔧 Troubleshooting

Common Function Composition Issues

Issue: Function composition errors
Solution: Add proper error handling
tsk_content = <<~TSK
  [error_fixes]
  # Add error handling to all pipelines
  safe_composition: @try_catch(@pipe(@data, [@step1, @step2]), @handle_error)
  
  # Use Maybe monad for nullable data
  maybe_composition: @maybe(@nullable_data, [@step1, @step2])
TSK
Issue: Performance problems with large datasets
Solution: Use streaming and parallel processing
tsk_content = <<~TSK
  [performance_fixes]
  # Use streaming for large datasets
  stream_composition: @stream_compose(@large_dataset, [@process, @validate])
  
  # Use parallel processing for independent operations
  parallel_composition: @parallel_compose(@data, [@op1, @op2, @op3])
TSK
Issue: Complex function composition
Solution: Break into smaller, composable functions
tsk_content = <<~TSK
  [complexity_fixes]
  # Break complex pipelines into smaller parts
  simple_pipeline_1: @pipe(@data, [@step1, @step2])
  simple_pipeline_2: @pipe(@simple_pipeline_1, [@step3, @step4])
  
  # Use function factories for reusable patterns
  reusable_pipeline: @factory(@config, @create_pipeline)
TSK

🎯 Summary

TuskLang's function composition provides powerful functional programming capabilities that integrate seamlessly with Ruby applications. By leveraging these operations, you can:

- Create complex transformation pipelines dynamically in configuration files - Build reusable function patterns with factories and currying - Handle errors gracefully with monadic composition - Optimize performance with caching and parallel processing - Implement functional programming patterns in your Ruby applications

The Ruby integration makes these operations even more powerful by combining TuskLang's declarative syntax with Ruby's rich functional programming features and libraries.

Remember: TuskLang function composition is designed to be expressive, performant, and Ruby-friendly. Use it to create dynamic, efficient, and maintainable functional programming configurations.

Key Takeaways: - Always handle errors in function compositions - Use caching for expensive operations - Keep functions pure when possible - Break complex pipelines into smaller, composable parts - Combine with Ruby's functional programming libraries for advanced functionality