Command line arguments, with types
Project description
argtyped
: Command Line Argument Parser, with Types
argtyped
is an command line argument parser with that relies on type annotations. It is built on
argparse
, the command line argument parser library built into
Python. Compared with argparse
, this library gives you:
- More concise and intuitive syntax, less boilerplate code.
- Type checking and IDE auto-completion for command line arguments.
- A drop-in replacement for
argparse
in most cases.
Since v0.4.0, argtyped
also supports parsing arguments defined with an attrs-class. See
Attrs Support for more details.
Installation
Install stable release from PyPI:
pip install argtyped
Or, install the latest commit from GitHub:
pip install git+https://github.com/huzecong/argtyped.git
Usage
With argtyped
, you can define command line arguments in a syntax similar to
typing.NamedTuple
. The syntax is intuitive and can
be illustrated with an example:
from typing import Optional
from typing_extensions import Literal # or directly import from `typing` in Python 3.8+
from argtyped import Arguments, Switch
from argtyped import Enum, auto
class LoggingLevels(Enum):
Debug = auto()
Info = auto()
Warning = auto()
Error = auto()
Critical = auto()
class MyArguments(Arguments):
model_name: str # required argument of `str` type
hidden_size: int = 512 # `int` argument with default value of 512
activation: Literal["relu", "tanh", "sigmoid"] = "relu" # argument with limited choices
logging_level: LoggingLevels = LoggingLevels.Info # using `Enum` class as choices
use_dropout: Switch = True # switch argument, enable with "--use-dropout" and disable with "--no-use-dropout"
dropout_prob: Optional[float] = 0.5 # optional argument, "--dropout-prob=none" parses into `None`
args = MyArguments()
This is equivalent to the following code with Python built-in argparse
:
import argparse
from enum import Enum
class LoggingLevels(Enum):
Debug = "debug"
Info = "info"
Warning = "warning"
Error = "error"
Critical = "critical"
parser = argparse.ArgumentParser()
parser.add_argument("--model-name", type=str, required=True)
parser.add_argument("--hidden-size", type=int, default=512)
parser.add_argument("--activation", choices=["relu", "tanh", "sigmoid"], default="relu")
parser.add_argument("--logging-level", choices=list(LoggingLevels), type=LoggingLevels, default="info")
parser.add_argument("--use-dropout", action="store_true", dest="use_dropout", default=True)
parser.add_argument("--no-use-dropout", action="store_false", dest="use_dropout")
parser.add_argument("--dropout-prob", type=lambda s: None if s.lower() == 'none' else float(s), default=0.5)
args = parser.parse_args()
Save the code into a file named main.py
. Suppose the following arguments are provided:
python main.py \
--model-name LSTM \
--activation sigmoid \
--logging-level debug \
--no-use-dropout \
--dropout-prob none
Then the parsed arguments will be equivalent to the following structure returned by argparse
:
argparse.Namespace(
model_name="LSTM", hidden_size=512, activation="sigmoid", logging_level="debug",
use_dropout=False, dropout_prob=None)
Arguments can also be pretty-printed:
>>> print(args)
<class '__main__.MyArguments'>
╔═════════════════╤══════════════════════════════════╗
║ Arguments │ Values ║
╠═════════════════╪══════════════════════════════════╣
║ model_name │ 'LSTM' ║
║ hidden_size │ 512 ║
║ activation │ 'sigmoid' ║
║ logging_level │ <MyLoggingLevels.Debug: 'debug'> ║
║ use_dropout │ False ║
║ dropout_prob │ None ║
║ label_smoothing │ 0.1 ║
║ some_true_arg │ True ║
║ some_false_arg │ False ║
╚═════════════════╧══════════════════════════════════╝
It is recommended though to use the args.to_string()
method, which gives you control of the table width.
Attrs Support (New)
The way we define the arguments is very similar to defining a dataclass or an attrs-class, so it seems natural to just write an attrs-class, and add parsing support to it.
To use argtyped
with attrs
, simply define an attrs-class as usual, and have it subclass AttrsArguments
. Here's
the same example above, but implemented with attrs-classes, and with some bells and whistles:
import attr # note: new style `attrs` syntax is also supported
from argtyped import AttrsArguments
def _convert_logging_level(s: str) -> LoggingLevels:
# Custom conversion function that takes the raw string value from the command line.
return LoggingLevels[s.lower()]
@attr.s(auto_attribs=True)
class MyArguments(AttrsArguments):
model_name: str = attr.ib(metadata={"positional": True}) # positional argument
# Or: `model_name: str = argtyped.positional_arg()`.
layer_sizes: List[int] = attr.ib(metadata={"nargs": "+"}) # other metadata are treated as `argparse` options
activation: Literal["relu", "tanh", "sigmoid"] = "relu"
logging_level: LoggingLevels = attr.ib(default=LoggingLevels.Info, converter=_convert_logging_level)
use_dropout: Switch = True
dropout_prob: Optional[float] = 0.5
_activation_fn: Callable[[float], float] = attr.ib(init=False) # `init=False` attributes are not parsed
@dropout_prob.validator # validators still work as you would expect
def _dropout_prob_validator(self, attribute, value):
if not 0.0 <= value <= 1.0:
raise ValueError(f"Invalid probability {value}")
@_activation_fn.default
def _activation_fn(self):
return _ACTIVATION_FNS[self.activation]
A few things to note here:
- You can define positional arguments by adding
"positional": True
as metadata. If this feels unnatural, you could also useargtyped.positional_arg()
, which takes the same arguments asattr.ib
. - You can pass additional options to
ArgumentParser.add_argument
by listing them as metadata as well. Note that these options take precedence overargtyped
's computed arguments, for example, sequence arguments (List[T]
) by default usesnargs="*"
, but you could override it with metadata. - Attributes with custom converters will not be parsed; its converter will be called with the raw string value from command line. If the attribute also has a default value, you should make sure that your converter works with both strings and the default value.
init=False
attributes are not treated as arguments, but they can be useful for storing computed values based on arguments.- The default value logic is the same as normal attrs classes, and thus could be different from non-attrs
argtyped
classes. For example, optional arguments are not considered to have an implicit default ofNone
, and no type validation is performed on default values.
Here are the (current) differences between an attrs-based arguments class (AttrsArguments
) versus the normal arguments
class (Arguments
):
AttrsArguments
supports positional arguments and custom options via metadata.AttrsArguments
handles default values with attrs, so there's no validation of default value types. This also means that nullable arguments must have an explicit default value ofNone
, otherwise it becomes a required argument.AttrsArguments
does not supportunderscore=True
.AttrsArguments
does not haveto_dict
,to_string
methods.AttrsArguments
needs to be called with the factoryparse_args
method to parse, whileArguments
parses command line arguments on construction.
Reference
The argtyped.Arguments
Class
The argtyped.Arguments
class is main class of the package, from which you should derive your custom class that holds
arguments. Each argument takes the form of a class attribute, with its type annotation and an optional default value.
When an instance of your custom class is initialized, the command line arguments are parsed from sys.argv
into values
with your annotated types. You can also provide the list of strings to parse by passing them as the parameter.
The parsed arguments are stored in an object of your custom type. This gives you arguments that can be auto-completed by the IDE, and type-checked by a static type checker like mypy.
The following example illustrates the keypoints:
class MyArgs(argtyped.Arguments):
# name: type [= default_val]
value: int = 0
args = MyArgs() # equivalent to `parser.parse_args()`
args = MyArgs(["--value", "123"]) # equivalent to `parser.parse_args(["--value", "123"])
assert isinstance(args, MyArgs)
Arguments.to_dict(self)
Convert the set of arguments to a dictionary (OrderedDict
).
Arguments.to_string(self, width: Optional[int] = None, max_width: Optional[int] = None)
Represent the arguments as a table.
width
: Width of the printed table. Defaults toNone
, which fits the table to its contents. An exception is raised when the table cannot be drawn with the given width.max_width
: Maximum width of the printed table. Defaults toNone
, meaning no limits. Must beNone
ifwidth
is notNone
.
argtyped.argument_specs
Return a dictionary mapping argument names to their specifications, represented as the argtyped.ArgumentSpec
type.
This is useful for programmatically accessing the list of arguments.
Argument Types
To summarize, whatever works for argparse
works here. The following types are supported:
-
Built-in types such as
int
,float
,str
. -
Boolean type
bool
. Accepted values (case-insensitive) forTrue
are:y
,yes
,true
,ok
; accepted values forFalse
are:n
,no
,false
. -
Choice types
Literal[...]
. A choice argument is essentially anstr
argument with limited choice of values. The ellipses can be filled with a tuple ofstr
s, or an expression that evaluates to a list ofstr
s:from argtyped import Arguments from typing_extensions import Literal class MyArgs(Arguments): foo: Literal["debug", "info", "warning", "error"] # 4 choices # argv: ["--foo=debug"] => foo="debug"
This is equivalent to the
choices
keyword inargparse.add_argument
.Note: The choice type was previously named
Choices
. This is deprecated in favor of theLiteral
type introduced in Python 3.8 and back-ported to 3.6 and 3.7 in thetyping_extensions
library.Choices
was removed since version 0.4.0. -
Enum types derived from
enum.Enum
. It is recommended to useargtyped.Enum
which uses the instance names as values:from argtyped import Enum class MyEnum(Enum): Debug = auto() # "debug" Info = auto() # "info" Warning = auto() # "warning"
-
Switch types
Switch
.Switch
arguments are likebool
arguments, but they don't take values. Instead, a switch argumentswitch
requires--switch
to enable and--no-switch
to disable:from argtyped import Arguments, Switch class MyArgs(Arguments): switch: Switch = True bool_arg: bool = False # argv: [] => flag=True, bool_arg=False # argv: ["--switch", "--bool-arg=false"] => flag=True, bool_arg=False # argv: ["--no-switch", "--bool-arg=true"] => flag=False, bool_arg=True # argv: ["--switch=false"] => WRONG # argv: ["--no-bool-arg"] => WRONG
-
List types
List[T]
, whereT
is any supported type except switch types. List arguments allow passing multiple values on the command line following the argument flag, it is equivalent to settingnargs="*"
inargparse
.Although there is no built-in support for other
nargs
settings such as"+"
(one or more) orN
(fixed number), you can add custom validation logic by overriding the__init__
method in yourArguments
subclass. -
Optional types
Optional[T]
, whereT
is any supported type except list or switch types. An optional argument will be filled withNone
if no value is provided. It could also be explicitly set toNone
by usingnone
as value in the command line:from argtyped import Arguments from typing import Optional class MyArgs(Arguments): opt_arg: Optional[int] # implicitly defaults to `None` # argv: [] => opt_arg=None # argv: ["--opt-arg=1"] => opt_arg=1 # argv: ["--opt-arg=none"] => opt_arg=None
-
Any other type that takes a single
str
as__init__
parameters. It is also theoretically possible to use a function that takes anstr
as input, but it's not recommended as it's not type-safe.
Composing Arguments
Classes
You can split your arguments into separate Arguments
classes and then compose them together by inheritance. A subclass
will have the union of all arguments in its base classes. If the subclass contains an argument with the same name as an
argument in a base class, then the subclass definition takes precedence. For example:
class BaseArgs(Arguments):
a: int = 1
b: Switch = True
class DerivedArgs(BaseArgs):
b: str
# args = DerivedArgs([]) # bad; `b` is required
args = DerivedArgs(["--b=1234"])
Caveat: For simplicity, we do not completely follow the C3 linearization algorithm that determines the class MRO in Python. Thus, it is a bad idea to have overridden arguments in cases where there's diamond inheritance.
If you don't understand the above, that's fine. Just note that generally, it's a bad idea to have too complicated inheritance relationships with overridden arguments.
Argument Naming Styles
By default argtyped
uses --kebab-case
(with hyphens connecting words), which is the convention for UNIX command line
tools. However, many existing tools use the awkward --snake_case
(with underscores connecting words), and sometimes
consistency is preferred over aesthetics. If you want to use underscores, you can do so by setting underscore=True
inside the parentheses where you specify base classes, like this:
class UnderscoreArgs(Arguments, underscore=True):
underscore_arg: int
underscore_switch: Switch = True
args = UnderscoreArgs(["--underscore_arg", "1", "--no_underscore_switch"])
The underscore settings only affect arguments defined in the class scope; (non-overridden) inherited arguments are not
affects. Thus, you can mix-and-match snake_case
and kebab-case
arguments:
class MyArgs(UnderscoreArgs):
kebab_arg: str
class MyFinalArgs(MyArgs, underscore=True):
new_underscore_arg: float
args = MyArgs(["--underscore_arg", "1", "--kebab-arg", "kebab", "--new_underscore_arg", "1.0"])
Notes
- Advanced
argparse
features such as subparsers, groups, argument lists, and custom actions are not supported. - Using switch arguments may result in name clashes: if a switch argument has name
arg
, there can be no argument with the nameno_arg
. - Optional types:
Optional
can be used withLiteral
:from argtyped import Arguments from typing import Literal, Optional class MyArgs(Arguments): foo: Optional[Literal["a", "b"]] # valid bar: Literal["a", "b", "none"] # also works but is less obvious
Optional[str]
would parse a value of"none"
(case-insensitive) intoNone
.
- List types:
List[Optional[T]]
is a valid type. For example:from argtyped import Arguments from typing import List, Literal, Optional class MyArgs(Arguments): foo: List[Optional[Literal["a", "b"]]] = ["a", None, "b"] # valid # argv: ["--foo", "a", "b", "none", "a", "b"] => foo=["a", "b", None, "a", "b"]
- List types cannot be nested inside a list or an optional type. Types such as
Optional[List[int]]
andList[List[int]]
are not accepted.
Under the Hood
This is what happens under the hood:
- When a subclass of
argtyped.Arguments
is constructed, type annotations and class-level attributes (i.e., the default values) are collected to form argument declarations. - After verifying the validity of declared arguments,
argtyped.ArgumentSpec
are created for each argument and stored within the subclass as the__arguments__
class attribute. - When an instance of the subclass is initialized, if it's the first time, an instance of
argparse.ArgumentParser
is created and arguments are registered with the parser. The parser is cached in the subclass as the__parser__
attribute. - The parser's
parse_args
method is invoked with eithersys.argv
or strings provided as parameters, returning parsed arguments. - The parsed arguments are assigned to
self
(the instance of theArguments
subclass being initialized).
Todo
- Support
action="append"
oraction="extend"
forList[T]
types.- Technically this is not a problem, but there's no elegant way to configure whether this behavior is desired.
- Throw (suppressible) warnings on using non-type callables as types.
- Support converting an
attrs
class intoArguments
. - Support forward references in type annotations.
MIT License
Copyright (c) 2020 Zecong Hu
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file argtyped-0.4.0.tar.gz
.
File metadata
- Download URL: argtyped-0.4.0.tar.gz
- Upload date:
- Size: 25.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.7.13
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c4d4086987d039ff5ad8f1716a9966c52c2e04f43e10ffccdf464ebd70ef6122 |
|
MD5 | 2dc01e92a54b0beb3d8ff2d0acf1c01b |
|
BLAKE2b-256 | 4573c8f3744b174211830f13f0cf8b1da88ea1c96330fc35c31dbf9ce719ae15 |
File details
Details for the file argtyped-0.4.0-py3-none-any.whl
.
File metadata
- Download URL: argtyped-0.4.0-py3-none-any.whl
- Upload date:
- Size: 19.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.7.13
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 809d671f6f4bbf75821fbd97885a743a8ede7145e069782b68d559209d6535ab |
|
MD5 | be5df3eec1e284c68d93a06b24e149a8 |
|
BLAKE2b-256 | 2654b283e8435075516f60834a7b0cca8c1702bc8824a57af59d68433befc72d |