# Copyright (c) 2019-2021 - for information on the respective copyright owner
# see the NOTICE file and/or the repository
# https://github.com/boschresearch/pylife
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
__author__ = "Johannes Mueller"
__maintainer__ = __author__
from pylife.core.data_validator import DataValidator
[docs]class PylifeSignal:
'''Base class for signal accessor classes
Parameters
----------
pandas_obj : pandas.DataFrame or pandas.Series
Notes
-----
Derived classes need to implement the method `_validate(self, obj)`
that gets `pandas_obj` as `obj` parameter. This `validate()` method
must raise an Exception (e.g. AttributeError or ValueError) in case
`obj` is not a valid DataFrame for the kind of signal.
For these validation :func:`fail_if_key_missing()` and
:func:`get_missing_keys()` might be helpful.
For a derived class you can register methods without modifying the
class' code itself. This can be useful if you want to make signal
accessor classes extendable.
See also
--------
:func:`fail_if_key_missing()`
:func:`get_missing_keys()`
:func:`register_method()`
'''
_method_dict = {}
def __init__(self, pandas_obj):
self._validator = DataValidator()
self._validate(pandas_obj, self._validator)
self._obj = pandas_obj
class _MethodCaller:
def __init__(self, method, obj):
self._method = method
self._obj = obj
def __call__(self, *args, **kwargs):
return self._method(self._obj, *args, **kwargs)
def __getattr__(self, itemname):
method = self._method_dict.get(itemname)
if method is None:
return super(PylifeSignal, self).__getattribute__(itemname)
return self._MethodCaller(method, self._obj)
@classmethod
def _register_method(cls, method_name):
def method_decorator(method):
if method_name in cls._method_dict.keys():
raise ValueError("Method '%s' already registered in %s" % (method_name, cls.__name__))
if hasattr(cls, method_name):
raise ValueError("%s already has an attribute '%s'" % (cls.__name__, method_name))
cls._method_dict[method_name] = method
return method_decorator
[docs]def register_method(cls, method_name):
'''Registers a method to a class derived from :class:`PyifeSignal`
Parameters
----------
cls : class
The class the method is registered to.
method_name : str
The name of the method
Raises
------
ValueError
if `method_name` is already registered for the class
ValueError
if `method_name` the class has already an attribute `method_name`
Notes
-----
The function is meant to be used as a decorator for a function
that is to be installed as a method for a class. The class is
assumed to contain a pandas object in `self._obj`.
Examples
--------
.. code-block:: python
import pandas as pd
import pylife as pl
@pd.api.extensions.register_dataframe_accessor('foo')
class FooAccessor(pl.signal.PyifeSignal):
def __init__(self, obj):
# self._validate(obj) could come here
self._obj = obj
@pl.signal.register_method(FooAccessor, 'bar')
def bar(df):
return pd.DataFrame({'baz': df['foo'] + df['bar']})
>>> df = pd.DataFrame({'foo': [1.0, 2.0], 'bar': [-1.0, -2.0]})
>>> df.foo.bar()
baz
0 0.0
1 0.0
'''
return cls._register_method(method_name)