#----------------------------------------------------------------------------- # Copyright (c) 2012 - 2019, Anaconda, Inc., and Bokeh Contributors. # All rights reserved. # # The full license is in the file LICENSE.txt, distributed with this software. #----------------------------------------------------------------------------- ''' Provide decorators help with define Bokeh validation checks. ''' #----------------------------------------------------------------------------- # Boilerplate #----------------------------------------------------------------------------- from __future__ import absolute_import, division, print_function, unicode_literals import logging log = logging.getLogger(__name__) #----------------------------------------------------------------------------- # Imports #----------------------------------------------------------------------------- # Standard library imports from functools import partial from six import string_types # External imports # Bokeh imports #----------------------------------------------------------------------------- # Globals and constants #----------------------------------------------------------------------------- __all__ = ( 'error', 'warning', ) #----------------------------------------------------------------------------- # Private API #----------------------------------------------------------------------------- def _validator(code_or_name, validator_type): ''' Internal shared implementation to handle both error and warning validation checks. Args: code code_or_name (int or str) : a defined error code or custom message validator_type (str) : either "error" or "warning" Returns: validation decorator ''' if validator_type == "error": from .errors import codes from .errors import EXT elif validator_type == "warning": from .warnings import codes from .warnings import EXT else: pass # TODO (bev) ValueError? def decorator(func): def wrapper(*args, **kw): extra = func(*args, **kw) if extra is None: return [] if isinstance(code_or_name, string_types): code = EXT name = codes[code][0] + ":" + code_or_name else: code = code_or_name name = codes[code][0] text = codes[code][1] return [(code, name, text, extra)] wrapper.validator_type = validator_type return wrapper return decorator _error = partial(_validator, validator_type="error") _warning = partial(_validator, validator_type="warning") #----------------------------------------------------------------------------- # General API #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Dev API #----------------------------------------------------------------------------- [docs]def error(code_or_name): ''' Decorator to mark a validator method for a Bokeh error condition Args: code_or_name (int or str) : a code from ``bokeh.validation.errors`` or a string label for a custom check Returns: callable : decorator for Bokeh model methods The function that is decorated should have a name that starts with ``_check``, and return a string message in case a bad condition is detected, and ``None`` if no bad condition is detected. Examples: The first example uses a numeric code for a standard error provided in ``bokeh.validation.errors``. This usage is primarily of interest to Bokeh core developers. .. code-block:: python from bokeh.validation.errors import REQUIRED_RANGES @error(REQUIRED_RANGES) def _check_no_glyph_renderers(self): if bad_condition: return "message" The second example shows how a custom warning check can be implemented by passing an arbitrary string label to the decorator. This usage is primarily of interest to anyone extending Bokeh with their own custom models. .. code-block:: python @error("MY_CUSTOM_WARNING") def _check_my_custom_warning(self): if bad_condition: return "message" ''' return _error(code_or_name) [docs]def warning(code_or_name): ''' Decorator to mark a validator method for a Bokeh error condition Args: code_or_name (int or str) : a code from ``bokeh.validation.errors`` or a string label for a custom check Returns: callable : decorator for Bokeh model methods The function that is decorated should have a name that starts with ``_check``, and return a string message in case a bad condition is detected, and ``None`` if no bad condition is detected. Examples: The first example uses a numeric code for a standard warning provided in ``bokeh.validation.warnings``. This usage is primarily of interest to Bokeh core developers. .. code-block:: python from bokeh.validation.warnings import MISSING_RENDERERS @warning(MISSING_RENDERERS) def _check_no_glyph_renderers(self): if bad_condition: return "message" The second example shows how a custom warning check can be implemented by passing an arbitrary string label to the decorator. This usage is primarily of interest to anyone extending Bokeh with their own custom models. .. code-block:: python @warning("MY_CUSTOM_WARNING") def _check_my_custom_warning(self): if bad_condition: return "message" ''' return _warning(code_or_name) #----------------------------------------------------------------------------- # Code #-----------------------------------------------------------------------------