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Assorted function decorators.

Project description

Assorted function decorators.

Latest release 20240412: @decorator: apply the decorated function name to the metadecorator.

Function ALL(func)

Include this function's name in its module's __all__ list.

Example:

from cs.deco import ALL

__all__ = []

def obscure_function(...):
    ...

@ALL
def well_known_function(...):
    ...

Function cached(*a, **kw)

Former name for @cachedmethod.

Function cachedmethod(*da, **dkw)

Decorator to cache the result of an instance or class method and keep a revision counter for changes.

The cached values are stored on the instance (self). The revision counter supports the @revised decorator.

This decorator may be used in 2 modes. Directly:

@cachedmethod
def method(self, ...)

or indirectly:

@cachedmethod(poll_delay=0.25)
def method(self, ...)

Optional keyword arguments:

  • attr_name: the basis name for the supporting attributes. Default: the name of the method.
  • poll_delay: minimum time between polls; after the first access, subsequent accesses before the poll_delay has elapsed will return the cached value. Default: None, meaning the value never becomes stale.
  • sig_func: a signature function, which should be significantly cheaper than the method. If the signature is unchanged, the cached value will be returned. The signature function expects the instance (self) as its first parameter. Default: None, meaning no signature function; the first computed value will be kept and never updated.
  • unset_value: the value to return before the method has been called successfully. Default: None.

If the method raises an exception, this will be logged and the method will return the previously cached value, unless there is not yet a cached value in which case the exception will be reraised.

If the signature function raises an exception then a log message is issued and the signature is considered unchanged.

An example use of this decorator might be to keep a "live" configuration data structure, parsed from a configuration file which might be modified after the program starts. One might provide a signature function which called os.stat() on the file to check for changes before invoking a full read and parse of the file.

Note: use of this decorator requires the cs.pfx module.

Function contextdecorator(*da, **dkw)

A decorator for a context manager function cmgrfunc which turns it into a decorator for other functions.

This supports easy implementation of "setup" and "teardown" code around other functions without the tedium of defining the wrapper function itself. See the examples below.

The resulting context manager accepts an optional keyword parameter provide_context, default False. If true, the context returned from the context manager is provided as the first argument to the call to the wrapped function.

Note that the context manager function cmgrfunc has not yet been wrapped with @contextmanager, that is done by @contextdecorator.

This decorator supports both normal functions and generator functions.

With a normal function the process is:

  • call the context manager with (func,a,kw,*da,**dkw), returning ctxt, where da and dkw are the positional and keyword parameters supplied when the decorator was defined.
  • within the context return the value of func(ctxt,*a,**kw) if provide_context is true or the value of func(*a,**kw) if not (the default)

With a generator function the process is:

  • obtain an iterator by calling func(*a,**kw)
  • for iterate over the iterator, yielding its results, by calling the context manager with (func,a,kw,**da,**dkw), around each next() Note that it is an error to provide a true value for provide_context if the decorated function is a generator function.

Some examples follow.

Trace the call and return of a specific function:

@contextdecorator
def tracecall(func, a, kw):
    """ Trace the call and return from some function.
        This can easily be adapted to purposes such as timing a
        function call or logging use.
    """
    print("call %s(*%r,**%r)" % (func, a, kw))
    try:
      yield
    except Exception as e:
      print("exception from %s(*%r,**%r): %s" % (func, a, kw, e))
      raise
    else:
      print("return from %s(*%r,**%r)" % (func, a, kw))

@tracecall
def f():
    """ Some function to trace.
    """

@tracecall(provide_context=True):
def f(ctxt, *a, **kw):
    """ A function expecting the context object as its first argument,
        ahead of whatever other arguments it would normally require.
    """

See who is making use of a generator's values, when a generator might be invoked in one place and consumed elsewhere:

from cs.py.stack import caller

@contextdecorator
def genuser(genfunc, *a, **kw):
    user = caller(-4)
    print(f"iterate over {genfunc}(*{a!r},**{kw!r}) from {user}")
    yield

@genuser
def linesof(filename):
    with open(filename) as f:
        yield from f

# obtain a generator of lines here
lines = linesof(__file__)

# perhaps much later, or in another function
for lineno, line in enumerate(lines, 1):
    print("line %d: %d words" % (lineno, len(line.split())))

Turn on "verbose mode" around a particular function:

import sys
import threading
from cs.context import stackattrs

class State(threading.local):
    def __init__(self):
        # verbose if stderr is on a terminal
        self.verbose = sys.stderr.isatty()

# per thread global state
state = State()

@contextdecorator
def verbose(func):
    with stackattrs(state, verbose=True) as old_attrs:
        if not old_attrs['verbose']:
            print(f"enabled verbose={state.verbose} for function {func}")
        # yield the previous verbosity as the context
        yield old_attrs['verbose']

# turn on verbose mode
@verbose
def func(x, y):
    if state.verbose:
        # print if verbose
        print("x =", x, "y =", y)

# turn on verbose mode and also pass in the previous state
# as the first argument
@verbose(provide_context=True):
def func2(old_verbose, x, y):
    if state.verbose:
        # print if verbose
        print("old_verbosity =", old_verbose, "x =", x, "y =", y)

Function contextual(func)

Wrap a simple function as a context manager.

This was written to support users of @strable, which requires its open_func to return a context manager; this turns an arbitrary function into a context manager.

Example promoting a trivial function:

>>> f = lambda: 3
>>> cf = contextual(f)
>>> with cf() as x: print(x)
3

Function decorator(deco)

Wrapper for decorator functions to support optional arguments.

The actual decorator function ends up being called as:

mydeco(func, *da, **dkw)

allowing da and dkw to affect the behaviour of the decorator mydeco.

Examples:

# define your decorator as if always called with func and args
@decorator
def mydeco(func, *da, arg2=None):
  ... decorate func subject to the values of da and arg2

# mydeco called with defaults
@mydeco
def func1(...):
  ...

@ mydeco called with nondefault arguments
@mydeco('foo', arg2='bah')
def func2(...):
  ...

Function default_params(*da, **dkw)

Decorator to provide factory functions for default parameters.

This decorator accepts the following keyword parameters:

  • _strict: default False; if true only replace genuinely missing parameters; if false also replace the traditional None placeholder value The remaining keyword parameters are factory functions providing the respective default values.

Atypical one off direct use:

@default_params(dbconn=open_default_dbconn,debug=lambda: settings.DB_DEBUG_MODE)
def dbquery(query, *, dbconn):
    dbconn.query(query)

Typical use as a decorator factory:

# in your support module
uses_ds3 = default_params(ds3client=get_ds3client)

# calling code which needs a ds3client
@uses_ds3
def do_something(.., *, ds3client,...):
    ... make queries using ds3client ...

This replaces the standard boilerplate and avoids replicating knowledge of the default factory as exhibited in this legacy code:

def do_something(.., *, ds3client=None,...):
    if ds3client is None:
        ds3client = get_ds3client()
    ... make queries using ds3client ...

Function fmtdoc(func)

Decorator to replace a function's docstring with that string formatted against the function's module __dict__.

This supports simple formatted docstrings:

ENVVAR_NAME = 'FUNC_DEFAULT'

@fmtdoc
def func():
    """Do something with os.environ[{ENVVAR_NAME}]."""
    print(os.environ[ENVVAR_NAME])

This gives func this docstring:

Do something with os.environ[FUNC_DEFAULT].

Warning: this decorator is intended for wiring "constants" into docstrings, not for dynamic values. Use for other types of values should be considered with trepidation.

Function logging_wrapper(*da, **dkw)

Decorator for logging call shims which bumps the stacklevel keyword argument so that the logging system chooses the correct frame to cite in messages.

Note: has no effect on Python < 3.8 because stacklevel only appeared in that version.

Function observable_class(property_names, only_unequal=False)

Class decorator to make various instance attributes observable.

Parameters:

  • property_names: an interable of instance property names to set up as observable properties. As a special case a single str can be supplied if only one attribute is to be observed.
  • only_unequal: only call the observers if the new property value is not equal to the previous proerty value. This requires property values to be comparable for inequality. Default: False, meaning that all updates will be reported.

Function OBSOLETE(*da, **dkw)

Decorator for obsolete functions.

Use:

@OBSOLETE
def func(...):

or

@OBSOLETE("new_func_name")
def func(...):

This emits a warning log message before calling the decorated function. Only one warning is emitted per calling location.

Class Promotable

A mixin class which supports the @promote decorator.

Method Promotable.promote(obj): Promote obj to an instance of cls or raise TypeError. This method supports the @promote decorator.

This base method will call the from_typename(obj) class factory method if present, where typename is obj.__class__.__name__.

Subclasses may override this method to promote other types, typically:

@classmethod
def promote(cls, obj):
    if isinstance(obj, cls):
        return obj
    ... various specific type promotions
    ... not done via a from_typename factory method
    # fall back to Promotable.promote
    return super().promote(obj)

Function promote(*da, **dkw)

A decorator to promote argument values automatically in annotated functions.

If the annotation is Optional[some_type] or Union[some_type,None] then the promotion will be to some_type but a value of None will be passed through unchanged.

The decorator accepts optional parameters:

  • params: if supplied, only parameters in this list will be promoted
  • types: if supplied, only types in this list will be considered for promotion

For any parameter with a type annotation, if that type has a .promote(value) class method and the function is called with a value not of the type of the annotation, the .promote method will be called to promote the value to the expected type.

Note that the Promotable mixin provides a .promote() method which promotes obj to the class if the class has a factory class method from_typename(obj) where typename is obj.__class__.__name__. A common case for me is lexical objects which have a from_str(str) factory to produce an instance from its textual form.

Additionally, if the .promote(value) class method raises a TypeError and value has a .as_typename attribute (where typename is the name of the type annotation), if that attribute is an instance method of value then promotion will be attempted by calling value.as_typename() otherwise the attribute will be used directly on the presumption that it is a property.

A typical promote(cls, obj) method looks like this:

@classmethod
def promote(cls, obj):
    if isinstance(obj, cls):
        return obj
    ... recognise various types ...
    ... and return a suitable instance of cls ...
    raise TypeError(
        "%s.promote: cannot promote %s:%r",
        cls.__name__, obj.__class__.__name__, obj)

Example:

>>> from cs.timeseries import Epoch
>>> from typeguard import typechecked
>>>
>>> @promote
... @typechecked
... def f(data, epoch:Epoch=None):
...     print("epoch =", type(epoch), epoch)
...
>>> f([1,2,3], epoch=12.0)
epoch = <class 'cs.timeseries.Epoch'> Epoch(start=0, step=12)

Example using a class with an as_P instance method:

>>> class P:
...   def __init__(self, x):
...     self.x = x
...   @classmethod
...   def promote(cls, obj):
...     raise TypeError("dummy promote method")
...
>>> class C:
...   def __init__(self, n):
...     self.n = n
...   def as_P(self):
...     return P(self.n + 1)
...
>>> @promote
... def p(p: P):
...   print("P =", type(p), p.x)
...
>>> c = C(1)
>>> p(c)
P = <class 'cs.deco.P'> 2

Note: one issue with this is due to the conflict in name between this decorator and the method it looks for in a class. The promote method must appear after any methods in the class which are decorated with @promote, otherwise the promote method supplants the name promote making it unavailable as the decorator. I usually just make .promote the last method.

Failing example:

class Foo:
    @classmethod
    def promote(cls, obj):
        ... return promoted obj ...
    @promote
    def method(self, param:Type, ...):
        ...

Working example:

class Foo:
    @promote
    def method(self, param:Type, ...):
        ...
    # promote method as the final method of the class
    @classmethod
    def promote(cls, obj):
        ... return promoted obj ...

Function strable(*da, **dkw)

Decorator for functions which may accept a str instead of their core type.

Parameters:

  • func: the function to decorate
  • open_func: the "open" factory to produce the core type if a string is provided; the default is the builtin "open" function. The returned value should be a context manager. Simpler functions can be decorated with @contextual to turn them into context managers if need be.

The usual (and default) example is a function to process an open file, designed to be handed a file object but which may be called with a filename. If the first argument is a str then that file is opened and the function called with the open file.

Examples:

@strable
def count_lines(f):
  return len(line for line in f)

class Recording:
  "Class representing a video recording."
  ...
@strable(open_func=Recording)
def process_video(r):
  ... do stuff with `r` as a Recording instance ...

Note: use of this decorator requires the cs.pfx module.

Release Log

Release 20240412: @decorator: apply the decorated function name to the metadecorator.

Release 20240326: default_params: update wrapper signature to mark the defaulted params as optional.

Release 20240316: Fixed release upload artifacts.

Release 20240314.1: New release with corrected install path.

Release 20240314: Tiny doc update.

Release 20240303: Promotable.promote: do not just handle str, handle anything with a from_typename factory method.

Release 20240211: Promotable: no longer abstract, provide a default promote() method which tries cls.from_str for str.

Release 20231129: @cachedmethod: ghastly hack for the revision attribute to accomodate objects which return None for missing attributes.

Release 20230331: @promote: pass None through for Optional parameters.

Release 20230212: New Promotable abstract class mixin, which requires the creation of a .promote(cls,obj)->cls class method.

Release 20230210: @promote: add support for .as_TypeName() instance method on the source object or a .as_TypeName property/attribut.

Release 20221214: @decorator: use functools.update_wrapper to propagate the decorated function's attributes to the wrapper (still legacy code for Python prior to 3.2).

Release 20221207: Small updates.

Release 20221106.1: @promote: support Optional[sometype] parameters.

Release 20221106: New @promote decorator to autopromote parameter values according to their type annotation.

Release 20220918.1: @default_param: append parameter descriptions to the docstring of the decorated function, bugfix name setting.

Release 20220918:

  • @OBSOLETE: tweak message format.
  • @default_params: docstring: simplify the example and improve the explaination.
  • @default_params: set the name of the wrapper function.

Release 20220905:

  • New @ALL decorator to include a function in all.
  • New @default_params decorator for making decorators which provide default argument values from callables.

Release 20220805: @OBSOLETE: small improvements.

Release 20220327: Some fixes for @cachedmethod.

Release 20220311: @cachedmethod: change the meaning of poll_delay=None to mean "never goes stale" as I had thought it already did.

Release 20220227: @cachedmethod: more paranoid access to the revision attribute.

Release 20210823: @decorator: preserve the name of the wrapped function.

Release 20210123: Syntax backport for older Pythons.

Release 20201202: @decorator: tweak test for callable(da[0]) to accord with the docstring.

Release 20201025: New @contextdecorator decorator for context managers to turn them into setup/teardown decorators.

Release 20201020:

  • @cachedmethod: bugfix cache logic.
  • @strable: support generator functions.

Release 20200725: Overdue upgrade of @decorator to support combining the function and decorator args in one call.

Release 20200517.2: Minor upgrade to @OBSOLETE.

Release 20200517.1: Tweak @OBSOLETE and @cached (obsolete name for @cachedmethod).

Release 20200517: Get warning() from cs.gimmicks.

Release 20200417:

  • @decorator: do not override doc on the decorated function, just provide default.
  • New @logging_wrapper which bumps the stacklevel parameter in Python 3.8 and above so that shims recite the correct caller.

Release 20200318.1: New @OBSOLETE to issue a warning on a call to an obsolete function, like an improved @cs.logutils.OBSOLETE (which needs to retire).

Release 20200318: @cachedmethod: tighten up the "is the value changed" try/except.

Release 20191012:

  • New @contextual decorator to turn a simple function into a context manager.
  • @strable: mention context manager requirement and @contextual as workaround.

Release 20191006: Rename @cached to @cachedmethod, leave compatible @cached behind which issues a warning (will be removed in a future release).

Release 20191004: Avoid circular import with cs.pfx by removing requirement and doing the import later if needed.

Release 20190905: Bugfix @deco: it turns out that you may not set the .module attribute on a property object.

Release 20190830.2: Make some getattr calls robust.

Release 20190830.1: @decorator: set the module of the wrapper.

Release 20190830: @decorator: set the module of the wrapper from the decorated target, aids cs.distinf.

Release 20190729: @cached: sidestep uninitialised value.

Release 20190601.1: @strable: fix the example in the docstring.

Release 20190601:

  • Bugfix @decorator to correctly propagate the docstring of the subdecorator.
  • Improve other docstrings.

Release 20190526: @decorator: add support for positional arguments and rewrite - simpler and clearer.

Release 20190512: @fmtdoc: add caveat against misuse of this decorator.

Release 20190404: New @fmtdoc decorator to format a function's doctsring against its module's globals.

Release 20190403:

  • @cached: bugfix: avoid using unset sig_func value on first pass.
  • @observable_class: further tweaks.

Release 20190322.1: @observable_class: bugfix init wrapper function.

Release 20190322:

  • New class decorator @observable_class.
  • Bugfix import of "warning".

Release 20190309: @cached: improve the exception handling.

Release 20190307.2: Fix docstring typo.

Release 20190307.1: Bugfix @decorator: final plumbing step for decorated decorator.

Release 20190307:

  • @decorator: drop unused arguments, they get used by the returned decorator.
  • Rework the @cached logic.

Release 20190220:

  • Bugfix @decorator decorator, do not decorate twice.
  • Have a cut at inheriting the decorated function's docstring.

Release 20181227:

  • New decoartor @strable for function which may accept a str instead of their primary type.
  • Improvements to @cached.

Release 20171231: Initial PyPI release.

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