A type safe dict utility class in python.
MIT. See License File.
params
is on the Python Package Index (PyPI):
pip install py-params
Params
represents a set of parameters modeled as a dict
with a fixed set of keys.
Default values are provided as class level attributes in Params
subclasses.
Parameter values can then be specified when constructing a Params
instance overriding the default values.
The parameter values can then be accessed both as attributes and dict
items,
however the Params
instance key set is closed for modification
thus an exception is raised when a parameter name is misspelled.
Accessing parameters not defined as class level attributes would raise an AttributeError
.
>>> import params as pp
>>> class TestParams(pp.Params):
... param_a = 1
... param_b = True
>>> params = TestParams() ## using the defaults
>>> params
{'param_a': 1, 'param_b': True}
>>> TestParams(param_a=2) ## setting a value for param_a
{'param_a': 2, 'param_b': True}
>>> params.param_a = 3 ## access as attribute or key
>>> params["param_a"] = 4
>>> params.param_a == params["param_a"]
True
>>> params.param_c
AttributeError: 'TestParams' object has no attribute 'test_c'
>>> params.param_c = 3
AttributeError: Setting unexpected parameter 'param_c' in Params instance 'TestParams'
>>> params["param_d"] = 4
AttributeError: Setting unexpected parameter 'param_d' in Params instance 'TestParams'
Params
instances can be used to generate CLI parser with argparse
:
>>> import params as pp
>>> class TestParams(pp.Params):
... number_of_things = pp.Param(None, doc="Specifies the number of things", dtype=int, required=True)
... use_feature_x = pp.Param(True, doc="whether to use feature X")
>>> parser = TestParams.to_argument_parser()
>>> parser.print_help()
usage: pydevconsole.py [-h] --number-of-things NUMBER_OF_THINGS
[--use-feature-x [USE_FEATURE_X]]
optional arguments:
-h, --help show this help message and exit
--number-of-things NUMBER_OF_THINGS
Specifies the number of things
--use-feature-x [USE_FEATURE_X]
whether to use feature X
>>> args = parser.parse_known_args(["--number-of-things", "7"])
>>> TestParams(args._get_kwargs())
{'number_of_things': 7, 'use_feature_x': True}
- 05.Feb.2021 - v0.10.2 - passing any
kwargs
toargparser
add_argument()
fromParam.__init__
- 10.Jan.2021 - v0.10.1 - YAML (de)serialization added; support for positional argument in argparse.
- 04.Apr.2020 -
WithParams
mixin added.- 31.Mar.2020 - support for generating
argparse
CLI parser. Hierarchy aggregation refactored.
As an illustration of how Params
could be used to reduce boilerplate code check:
- kpe/params-flow - utilities for reducing keras boilerplate code in custom layers
- kpe/bert-for-tf2 - BERT implementation using the TensorFlow 2 Keras API