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* Moving the fancy "Parameters" parameter lookup class to its own module.

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From now on, use it as wpylib.params.flat class.
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wirawan 14 years ago
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commit 6641410d89
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  1. 10
      params/__init__.py
  2. 301
      params/params_flat.py
  3. 24
      params/params_flat_test.py

10
params/__init__.py
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# $Id: __init__.py,v 1.1 2010-09-30 16:16:38 wirawan Exp $
#
# wpylib.params module
# Created: 20100930
# Wirawan Purwanto
"""Parameter-related stuff."""
from wpylib.params.params_flat import Parameters as flat

301
params/params_flat.py
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# $Id: params_flat.py,v 1.1 2010-09-30 16:16:38 wirawan Exp $
#
# wpylib.params.params_flat module
# Created: 20100930
# Wirawan Purwanto
import inspect # for self-introspection of call stack
import weakref
from wpylib.sugar import ifelse
"""
This module specializes in handling parameters that are defined in
a 'flat' namespace, i.e. no nested name scoping.
NOTE:
I might explore the idea of nested parameter space later, should a need
for that arise.
This nested space is much more complicated, and will require
copy-on-write kind of support to reduce recursively copying parameters
whenever the set of parameters is passed from one subroutine to another.
"""
class Parameters(dict):
"""A standardized way to define and/or pass parameters (with possible
default values) among routines.
This class provides a very flexible lookup scheme for a parameter with
a given name.
It scans through the namescopes (dicts) in a deterministic and sequential
order, returning the first one found.
This, hopefully, gets rid of kitchen-sink parameter passing, at least from
programmer's point of view.
WARNING: This object is derived from python dict with ALL method names removed,
so as to avoid collosion of these names with user-defined parameters with the
same name.
Names reserved by this class begin and end with an underscore.
Names reserved by python begin and end with two underscores.
So, avoid specifying parameters with both leading and trailing underscores.
WARNING: Be careful modifying this class; endless recursive calls are
possible.
Some uses:
def stuff(params=None, **kwparams):
# `params' defines the standard way of passing parameters, which is
# via a Parameters object.
# `kwparams' determine a quick way of temporarily overriding a parameter
# value.
prm = Parameters(kwparams, params, global_defaults)
for step in prm.steps:
...
Parameters can also be updated in this way:
a = Parameters(...)
updates = {'nblk': 7, 'nbasis': 32}
a += updates
or, to call a function with a combination of parameters:
Reserved private members of the Parameters object:
* _no_null_ = (True/False, default False) look for non-null (non-"None") values
in all the parameter lists until one is found.
* _list_ = (list) the list of parameter dicts to search from.
* _kwparam_ = (string, default "_opts_") the default name of the function argument
that will hold excess named arguments.
Used in _create_() function below.
If this is set to None, we will not use this feature.
* _userparam_ = (string, default "_p") the default name of the function argument
that will contain Parameters-like object given by the user.
Used in _create_() function below.
If this is set to None, we will not use this feature.
The most overriding list of parameters, as provided via excess key=value
arguments in creating this Parameters object, are stored in "self".
"""
class _self_weakref_:
"""A minimal proxy object, just enough to get a weakref to the 'self' object
below to be accesible via a few dict-like lookup mechanisms.
Also needed to avoid recursive `in' and [] get operators below."""
def __init__(self, obj):
self.ref = weakref.ref(obj)
def __contains__(self, key):
return dict.__contains__(self.ref(), key)
def __getitem__(self, key):
return dict.__getitem__(self.ref(), key)
def __init__(self, *_override_dicts_, **_opts_):
"""
Creates a new Parameters() object.
The unnamed arguments are taken to be dict-like objects from which we will
search for parameters.
We silently ignore `None' values which are passed in this way.
Parameters will be searched in left-to-right order of these dict-like
objects.
Then the keyword-style arguments passed on this constructor will become
the most overriding options.
The dict-like objects must contain the following functionalities:
* for key in obj:
...
(in other words, the __iter__() method).
* key in obj
* obj[key]
That's it!
Example:
defaults = { 'walltime': '6:00:00', 'nwlk': 100 }
# ...
p = Parameters(defaults, walltime='7:00:00', nblk=300)
Then when we want to use it:
>> p.nwlk
100
>> p.walltime
'7:00:00'
>> p.nblk
300
Options:
* _no_null_ = if True, look for the first non-None value.
* _flatten_ = will flatten the key-value pairs.
Note that this may make the Parameters object unnecessarily large in memory.
Additionally, this means that the updates in the contents of the dicts
passed as the _override_dicts_ can no longer be reflected in this object
because of the shallow copying involved here.
* _kwparam_
* _userparam_
At present, the `flatten' attribute will not be propagated to the child
Parameters objects created by this parent object.
"""
# Remove standard dict procedure names not beginning with "_":
for badkw in self.__dict__:
if not badkw.startswith("_"):
del self.__dict__[badkw]
# Store the user-defined overrides in its own container:
dict.clear(self)
if _opts_.get('_flatten_', False):
for p in _override_dicts_:
dict.update(self, p)
dict.update(self, _opts_)
else:
dict.update(self, _opts_)
# WARNING: Using weakref proxy is important:
# - to allow clean deletion of Parameters() objects when not needed
# - to avoid recursive 'in' and 'get[]' operators.
paramlist = (Parameters._self_weakref_(self),) + _override_dicts_ #+ tuple(deflist))
#paramlist = (self,) + _override_dicts_ #+ tuple(deflist))
self.__dict__["_list_"] = [ p for p in paramlist if p != None ]
self.__dict__["_kwparam_"] = _opts_.get("_kwparam_", "_opts_")
self.__dict__["_userparam_"] = _opts_.get("_userparam_", "_p")
self.__dict__["_no_null_"] = ifelse(_opts_.get("_no_null_"), True, False)
# Finally, filter out reserved keywords from the dict:
for badkw in ("_kwparam_", "_userparam_", "_no_null_", "_flatten_"):
#if badkw in self: del self[badkw] -- recursive!!!
if dict.__contains__(self,badkw): del self[badkw]
def _copy_(self):
"""Returns a copy of the Parameters() object."""
return Parameters(_no_null_=self._no_null_,
_kwparam_=self._kwparam_,
_userparam_=self._userparam_,
*self._list_[1:],
**self)
def __getattr__(self, key):
"""Allows options to be accessed in attribute-like manner, like:
opt.niter = 3
instead of
opt['niter'] = 3
"""
if self._no_null_:
for ov in self._list_:
if key in ov and ov[key] != None: return ov[key]
else:
for ov in self._list_:
if key in ov: return ov[key]
# Otherwise: -- but most likely this will return attribute error:
return dict.__getattribute__(self, key)
def __setattr__(self, key, value):
"""This method always sets the value on the object's dictionary.
Values set will override any values set in the input parameter lists."""
self[key] = value
def __contains__(self, key):
if self._no_null_:
for ov in self._list_:
if key in ov and ov[key] != None: return True
else:
for ov in self._list_:
if key in ov: return True
return False
def __getitem__(self, key):
if self._no_null_:
for ov in self._list_:
if key in ov and ov[key] != None: return ov[key]
else:
for ov in self._list_:
if key in ov: return ov[key]
raise KeyError, "Cannot find parameter `%s'" % key
#def __setitem__(self, key, value): # -- inherited from dict
# self._prm_[key] = value
# TODO in the future for iterative accesses:
# -- not that essential because we know the name of
# the parameters we want to get:
#def __iter__(self): # -- inherited from dict
# """Returns the iterator over key-value pairs owned by this object.
# This does NOT return key-value pairs owned by the _override_dicts_.
# """
# return self._prm_.__iter__()
#def _iteritems_(self):
# return self._prm_.iteritems()
def _update_(self, srcdict):
"""Updates the most overriding parameters with key-value pairs from
srcdict.
Srcdict can be either a dict-derived object or a Parameters-derived
object."""
dict.update(self, srcdict)
def __add__(self, srcdict):
"""Returns a copy of the Parameters() object, with the most-overriding
parameters updated from the contents of srcdict."""
rslt = self._copy_()
rslt._update_(srcdict)
return rslt
def _create_(self, kwparam=None, userparam=None, *defaults):
"""Creates a new Parameters() object for standardized function-level
parameter lookup.
This routine *must* be called by the function where we want to access these
parameters, and where some parameters are to be overriden via function
arguments, etc.
The order of lookup is definite:
* local variables of the calling subroutine will take precedence
* the excess keyword-based parameters,
* user-supplied Parameters-like object, which is
* the dicts (passed in the `defaults' unnamed parameter list) is searched
*last*.
I suggest that this is used only as a last-effort safety net.
Ideally, the creating Parameters object itself should contain the
'factory defaults', as shown in the example below.
class Something(object):
def __init__(self, ...):
# self.opts holds the factory default
self.opts = Parameters()
self.opts.cleanup = True # example
def doit(self, src=None, info=None,
_defaults_=dict(src="source.txt", info="INFO.txt", debug=1),
**_opts_):
# FIXME: use self-introspection to reduce kitchen-sink params here:
p = self.opts._create_(_defaults_)
# ^ This will create an equivalent of:
# Parameters(locals(), _opts_, _opts_.get('opts'), self.opts, _defaults)
# Now use it:
if p.cleanup:
... do something
"""
# Look up the stack of the calling function in order to retrieve its
# local variables
from inspect import stack
caller = stack()[1][0] # one frame up; element-0 is the stack frame
if kwparam == None: kwparam = self._kwparam_
if userparam == None: userparam = self._userparam_
# local variables will be the first scope to look for
localvars = caller.f_locals
contexts = [ localvars ]
# then _opts_ excess-keyword parameters (see example of doit() above)
if kwparam in localvars:
_opts_ = localvars[kwparam]
contexts.append(_opts_)
else:
_opts_ = {}
# then opts, an explicitly-defined argument which contain a set of parameters
if userparam in localvars:
opts = localvars[userparam]
contexts.append(opts)
else:
opts = {}
if userparam in _opts_:
contexts.append(_opts_[userparam])
# then this own Parameters data will come here:
contexts.append(self)
# then any last-minute defaults
contexts += [ d for d in defaults ]
# Now construct the Parameters() class for this calling function:
return Parameters(_kwparam_=kwparam, _userparam_=userparam, *contexts)
#def __dict__(self):
# return self._prm_

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params/params_flat_test.py
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# $Id: params_flat_test.py,v 1.1 2010-09-30 16:16:38 wirawan Exp $
# 20100930
from wpylib.params import flat as params
def test1():
defaults = {
'nbasis': 320,
'npart': 37,
'deltau': 0.025,
}
p = params(defaults, nbasis=332)
print "self-defined values = ", p
print "nbasis = ", p.nbasis
print "npart = ", p.npart
print "deltau = ", p.deltau
p.deltau = 0.01
print "new deltau = ", p.deltau
if __name__ == "__main__":
test1()
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