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# ==================================================================================================================== #
# _____ _ _ ____ _ ___ _ _ _ _ _ #
# _ __ _ |_ _|__ ___ | (_)_ __ __ _ / ___| | |_ _| / \ | |__ ___| |_ _ __ __ _ ___| |_(_) ___ _ __ #
# | '_ \| | | || |/ _ \ / _ \| | | '_ \ / _` || | | | | | / _ \ | '_ \/ __| __| '__/ _` |/ __| __| |/ _ \| '_ \ #
# | |_) | |_| || | (_) | (_) | | | | | | (_| || |___| |___ | | / ___ \| |_) \__ \ |_| | | (_| | (__| |_| | (_) | | | | #
# | .__/ \__, ||_|\___/ \___/|_|_|_| |_|\__, (_)____|_____|___/_/ \_\_.__/|___/\__|_| \__,_|\___|\__|_|\___/|_| |_| #
# |_| |___/ |___/ #
# ==================================================================================================================== #
# Authors: #
# Patrick Lehmann #
# #
# License: #
# ==================================================================================================================== #
# Copyright 2017-2024 Patrick Lehmann - Bötzingen, Germany #
# Copyright 2014-2016 Technische Universität Dresden - Germany, Chair of VLSI-Design, Diagnostics and Architecture #
# #
# 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. #
# #
# SPDX-License-Identifier: Apache-2.0 #
# ==================================================================================================================== #
#
"""
Valued tuple-flag arguments represent a name and a value as a 2-tuple.
.. seealso::
* For flags with a value. |br|
|rarr| :mod:`~pyTooling.CLIAbstraction.ValuedFlag`
* For flags that have an optional value. |br|
|rarr| :mod:`~pyTooling.CLIAbstraction.NamedOptionalValuedFlag`
"""
from typing import Any
try:
from pyTooling.Decorators import export
from pyTooling.CLIAbstraction.Argument import NamedTupledArgument
except (ImportError, ModuleNotFoundError): # pragma: no cover
print("[pyTooling.Versioning] Could not import from 'pyTooling.*'!")
try:
from Decorators import export
from CLIAbstraction.Argument import NamedTupledArgument
except (ImportError, ModuleNotFoundError) as ex: # pragma: no cover
print("[pyTooling.Versioning] Could not import directly!")
raise ex
@export
class ShortTupleFlag(NamedTupledArgument, pattern="-{0}"):
"""
Represents a :class:`ValuedTupleArgument` with a single dash in front of the switch name.
**Example:**
* ``-file file1.txt``
"""
def __init_subclass__(cls, *args: Any, pattern: str = "-{0}", **kwargs: Any):
kwargs["pattern"] = pattern
super().__init_subclass__(*args, **kwargs)
def __new__(cls, *args: Any, **kwargs: Any):
if cls is ShortTupleFlag:
raise TypeError(f"Class '{cls.__name__}' is abstract.")
return super().__new__(cls, *args, **kwargs)
@export
class LongTupleFlag(NamedTupledArgument, pattern="--{0}"):
"""
Represents a :class:`ValuedTupleArgument` with a double dash in front of the switch name.
**Example:**
* ``--file file1.txt``
"""
def __init_subclass__(cls, *args: Any, pattern: str = "--{0}", **kwargs: Any):
kwargs["pattern"] = pattern
super().__init_subclass__(*args, **kwargs)
def __new__(cls, *args: Any, **kwargs: Any):
if cls is LongTupleFlag:
raise TypeError(f"Class '{cls.__name__}' is abstract.")
return super().__new__(cls, *args, **kwargs)
@export
class WindowsTupleFlag(NamedTupledArgument, pattern="/{0}"):
"""
Represents a :class:`ValuedTupleArgument` with a single slash in front of the switch name.
**Example:**
* ``/file file1.txt``
"""
def __init_subclass__(cls, *args: Any, pattern: str = "/{0}", **kwargs: Any):
kwargs["pattern"] = pattern
super().__init_subclass__(*args, **kwargs)
def __new__(cls, *args: Any, **kwargs: Any):
if cls is WindowsTupleFlag:
raise TypeError(f"Class '{cls.__name__}' is abstract.")
return super().__new__(cls, *args, **kwargs)
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