random_choices

Instructions

Implementation Reference

• src/random_number_mcp/tools.py:57-80 (handler)

  Core implementation of random_choices: calls random.choices() with validation for population, k, and weights.

  def random_choices(
      population: list[Any], k: int = 1, weights: list[int | float] | None = None
  ) -> list[Any]:
      """Choose k items from population with replacement, optionally weighted.
  
      Args:
          population: List of items to choose from
          k: Number of items to choose (default 1)
          weights: Optional weights for each item (default None for equal weights)
  
      Returns:
          List of k chosen items
  
      Raises:
          ValueError: If population is empty, k < 0, or weights length doesn't match
          TypeError: If k is not an integer
      """
      validate_list_not_empty(population, "population")
      validate_positive_int(k, "k")
  
      if weights is not None:
          validate_weights_match_population(population, weights)
  
      return random.choices(population, weights=weights, k=k)

• src/random_number_mcp/server.py:41-65 (handler)

  MCP server registration of random_choices tool with app.tool() decorator; handles weights as optional JSON string.

  @app.tool()
  def random_choices(
      population: list[str | int | float | bool],
      k: int = 1,
      weights: list[int | float] | str | None = None,
  ) -> list[str | int | float | bool]:
      """Choose k items from population with replacement, optionally weighted.
  
      Args:
          population: List of items to choose from
          k: Number of items to choose (default 1)
          weights: Optional weights for each item (default None for equal weights)
  
      Returns:
          List of k chosen items
      """
      numeric_weights: list[int | float] | None = None
      if isinstance(weights, str):
          try:
              numeric_weights = json.loads(weights)
          except json.JSONDecodeError as e:
              raise ValueError(f"Invalid JSON string for weights: {weights}") from e
      else:
          numeric_weights = weights
      return tools.random_choices(population, k, numeric_weights)

• src/random_number_mcp/server.py:41-41 (registration)

  @app.tool() decorator registration of the random_choices function as an MCP tool.

  @app.tool()

• src/random_number_mcp/utils.py:12-18 (helper)

  validate_positive_int: validates that k is a non-negative integer.

  def validate_positive_int(value: int, name: str) -> None:
      """Validate that a value is a positive integer."""
      if not isinstance(value, int):
          raise TypeError(f"{name} must be an integer, got {type(value).__name__}")
      if value < 0:
          raise ValueError(f"{name} must be non-negative, got {value}")

• src/random_number_mcp/utils.py:26-34 (helper)

  validate_weights_match_population: validates weights list length matches population length.

  def validate_weights_match_population(
      population: list[Any], weights: list[int | float]
  ) -> None:
      """Validate that weights list matches population length."""
      if len(weights) != len(population):
          raise ValueError(
              f"Weights list length ({len(weights)}) must match "
              f"population length ({len(population)})"
          )