Pydargs allows configuring a dataclass through command line arguments.
Project description
pydargs
Pydargs allows configuring a (Pydantic) dataclass through command line arguments.
Installation
Pydargs can be installed with your favourite package manager. For example:
pip install pydargs
Usage
A minimal usage example would be:
from dataclasses import dataclass
from pydargs import parse
@dataclass
class Config:
number: int
some_string: str = "abc"
if __name__ == "__main__":
config = parse(Config)
After which this entrypoint can be called with
entrypoint --number 42
or
entrypoint --number 42 --some-string abcd
ArgumentParser arguments
It's possible to pass additional arguments to the underlying argparse.ArgumentParser
instance by providing them
as keyword arguments to the parse
function. For example:
config = parse(Config, prog="myprogram", allow_abbrev=False)
will disable abbreviations for long options and set the program name to myprogram
in help messages. For an extensive list of accepted arguments, see the argparse docs.
Supported Field Types
The dataclass can have fields of the base types: int
, float
, str
, bool
, as well as:
- Enums or literals comprised of those types.
- Bytes, with an optional
encoding
metadata field:a_value: bytes = field(metadata=dict(encoding="ascii"))
, which defaults to utf-8. - Date and datetime, with an optional
date_format
metadata field:your_date: date = field(metadata=dict(date_format="%m-%d-%Y"))
. When not provided dates in ISO 8601 format are accepted. - Lists of those types, either denoted as e.g.
list[int]
orSequence[int]
. Multiple arguments to anumbers: list[int]
field can be provided as--numbers 1 2 3
. A list-field without a default will require at least a single value to be provided. If a default is provided, it will be completely replaced by any arguments, if provided. - Optional types, denoted as e.g.
typing.Optional[int]
orint | None
(for Python 3.10 and above). Any argument passed is assumed to be of the provided type and can never beNone
. - Unions of types, denoted as e.g.
typing.Union[int, str]
orint | str
. Each argument will be parsed into the first type that returns a valid result. Note that this means thatstr | int
will always result in a value of typestr
. - Any other type that can be instantiated from a string, such as
Path
. - Dataclasses that, in turn, contain fields of supported types. See Nested Dataclasses.
Metadata
Additional options can be provided to the dataclass field metadata.
The following metadata fields are supported:
positional
Set positional=True
to create a positional argument instead of an option.
from dataclasses import dataclass, field
@dataclass
class Config:
argument: str = field(metadata=dict(positional=True))
as_flags
Set as_flags=True
for a boolean field:
from dataclasses import dataclass, field
@dataclass
class Config:
verbose: bool = field(default=False, metadata=dict(as_flags=True))
which would create the arguments --verbose
and --no-verbose
to
set the value of verbose
to True
or False
respectively, instead
of a single option that requires a value like --verbose True
.
parser
Provide a custom type converter that parses the argument into the desired type. For example:
from dataclasses import dataclass, field
from json import loads
@dataclass
class Config:
list_of_numbers: list[int] = field(metadata=dict(parser=loads))
This would parse --list-of-numbers [1, 2, 3]
into the list [1, 2, 3]
. Note that the error message returned
when providing invalid input is lacking any details. Also, no validation is performed to verify that the returned
type matches the field type. In the above example, --list-of-numbers '{"a": "b"}'
would result in list_of_numbers
being the dictionary {"a": "b"}
without any kind of warning.
short_option
Provide a short option for a field, which can be used as an alternative to the long option. For example,
from dataclasses import dataclass, field
@dataclass
class Config:
a_field_with_a_long_name: int = field(metadata=dict(short_option="-a"))
would allow using -a 42
as an alternative to --a-field-with-a-long-name 42
.
Ignoring fields
Fields can be ignored by adding the ignore_arg
metadata field:
@dataclass
class Config:
number: int
ignored: str = field(metadata=dict(ignore_arg=True))
When indicated, this field is not added to the parser and cannot be overridden with an argument.
help
Provide a brief description of the field, used in the help messages generated by argparse.
For example, calling your_program -h
with the dataclass below,
from dataclasses import dataclass, field
@dataclass
class Config:
an_integer: int = field(metadata=dict(help="any integer you like"))
would result in a message like:
usage: your_program [-h] [--an-integer AN_INTEGER]
optional arguments:
-h, --help show this help message and exit
--an-integer AN_INTEGER any integer you like
metavar
Override the displayed name of an argument in the help messages generated by argparse, as documented here.
For example, with the following dataclass,
from dataclasses import dataclass, field
@dataclass
class Config:
an_integer: int = field(metadata=dict(metavar="INT"))
calling your_program -h
would result in a message like:
usage: your_program [-h] [--an-integer INT]
optional arguments:
-h, --help show this help message and exit
--an-integer INT
Nested Dataclasses
Dataclasses may be nested; the type of a dataclass field may be another dataclass type:
from dataclasses import dataclass
@dataclass
class Config:
field_a: int
field_b: str = "abc"
@dataclass
class Base:
config: Config
verbose: bool = False
Argument names of fields of the nested dataclass are prefixed with the field name of the nested dataclass in the base
dataclass. Calling pydargs.parse(Base, ["-h"])
will result in somthing like:
usage: your_program.py [-h] --config-field-a CONFIG_FIELD_A
[--config-field-b CONFIG_FIELD_B]
[--verbose VERBOSE]
options:
-h, --help show this help message and exit
--verbose VERBOSE (default: False)
config:
--config-field-a CONFIG_FIELD_A
--config-field-b CONFIG_FIELD_B
(default: abc)
Please be aware of the following:
- The default (factory) of fields with a dataclass type is ignored by pydargs, which may yield unexpected results.
E.g., in the example above,
config: Config = field(default_factory=lambda: Config(field_b="def"))
will not result in a default of "def" for field_b when parsed by pydargs. Instead, setfield_b: str = "def"
in the definition ofConfig
. If you must add a default, for example for instantiating your dataclass elsewhere, doconfig: Config = field(default_factory=Config)
, assuming that all fields inConfig
have a default. - Nested dataclasses can not be positional (although fields of the nested dataclass can be).
- Argument names must not collide. In the example above, the
Base
class should not contain a field namedconfig_field_a
.
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