Source code for apache_beam.utils.annotations

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"""Deprecated and experimental annotations.

Experimental: Signifies that a public API (public class, method or field) is
subject to incompatible changes, or even removal, in a future release. Note that
the presence of this annotation implies nothing about the quality or performance
of the API in question, only the fact that the API or behavior may change in any
way.

Deprecated: Signifies that users are discouraged from using a public API
typically because a better alternative exists, and the current form might be
removed in a future version.

Usage:
For internal use only; no backwards-compatibility guarantees.

Annotations come in two flavors: deprecated and experimental

The 'deprecated' annotation requires a 'since" parameter to specify
what version deprecated it.
Both 'deprecated' and 'experimental' annotations can specify the
current recommended version to use by means of a 'current' parameter.

The following example illustrates how to annotate coexisting versions of the
same function 'multiply'.::

  def multiply(arg1, arg2):
    print(arg1, '*', arg2, '=', end=' ')
    return arg1*arg2

# This annotation marks 'old_multiply' as deprecated since 'v.1' and suggests
# using 'multiply' instead.::

  @deprecated(since='v.1', current='multiply')
  def old_multiply(arg1, arg2):
    result = 0
    for i in xrange(arg1):
        result += arg2
    print(arg1, '*', arg2, '(the old way)=', end=' ')
    return result

# This annotation marks 'exp_multiply' as experimental and suggests
# using 'multiply' instead.::

  @experimental(since='v.1', current='multiply')
  def exp_multiply(arg1, arg2):
    print(arg1, '*', arg2, '(the experimental way)=', end=' ')
    return (arg1*arg2)*(arg1/arg2)*(arg2/arg1)

# Set a warning filter to control how often warnings are produced.::

  warnings.simplefilter("always")
  print(multiply(5, 6))
  print(old_multiply(5,6))
  print(exp_multiply(5,6))
"""

from __future__ import absolute_import

import warnings
from functools import partial
from functools import wraps

# Produce only the first occurrence of matching warnings regardless of
# location per line of execution. Since the number of lines of execution
# depends on the concrete runner, the number of warnings produced will
# vary depending on the runner.
warnings.simplefilter("once")


[docs]def annotate(label, since, current, extra_message): """Decorates a function with a deprecated or experimental annotation. Args: label: the kind of annotation ('deprecated' or 'experimental'). since: the version that causes the annotation. current: the suggested replacement function. extra_message: an optional additional message. Returns: The decorator for the function. """ def _annotate(fnc): @wraps(fnc) def inner(*args, **kwargs): if label == 'deprecated': warning_type = DeprecationWarning else: warning_type = FutureWarning message = '%s is %s' % (fnc.__name__, label) if label == 'deprecated': message += ' since %s' % since message += '. Use %s instead.' % current if current else '.' if extra_message: message += ' ' + extra_message warnings.warn(message, warning_type, stacklevel=2) return fnc(*args, **kwargs) return inner return _annotate
# Use partial application to customize each annotation. # 'current' will be optional in both deprecated and experimental # while 'since' will be mandatory for deprecated. deprecated = partial(annotate, label='deprecated', current=None, extra_message=None) experimental = partial(annotate, label='experimental', current=None, since=None, extra_message=None)