Command Line Interface Generator
Project description
clig - CLI Generator
A single module, pure python, Command Line Interface Generator (Complete documentation).
Installation
Install with pip:
pip install clig
Or just download the module.
User guide
clig is a single module, written in pure python, that wraps around the
stdlib module argparse to
generate command line interfaces through simple functions.
If you know how to use
argparse, you may want to
use clig.
Basic usage
Create or import some function and call
clig.run()
with it:
# example01.py
import clig
def printperson(name, title="Mister"):
print(f"{title} {name}")
clig.run(printperson)
In general, the function arguments that have a "default" value are turned into
optional flagged (--) command line arguments, while the "non default" will
be positional arguments.
> python example01.py -h
usage: printperson [-h] [--title TITLE] name
positional arguments:
name
options:
-h, --help show this help message and exit
--title TITLE
The script can then be used in the same way as used with
argparse:
> python example01.py John
Mister John
> python example01.py Maria --title Miss
Miss Maria
You can also pass arguments in code (like with the original
parse_args()
method)
>>> import clig
>>> def printperson(name, title="Mister"):
... print(f"{title} {name}")
...
>>> clig.run(printperson, ["Isaac", "--title", "Sir"])
Sir Isaac
The
clig.run()
function also accepts
other arguments to customize the interface
Helps
Arguments and command Helps are taken from the docstring when possible:
# example02.py
import clig
def greetings(name, greet="Hello"):
"""Description of the command: A greeting prompt!
Args:
name: The name to greet
greet: The greeting used. Defaults to "Hello".
"""
print(f"Greetings: {greet} {name}!")
clig.run(greetings)
> python example02.py --help
usage: greetings [-h] [--greet GREET] name
Description of the command: A greeting prompt!
positional arguments:
name The name to greet
options:
-h, --help show this help message and exit
--greet GREET The greeting used. Defaults to "Hello".
There is an internal list of docstring templates from which you can choose if the inferred docstring is not correct. It is also possible to specify your own custom docstring template.
Argument inference
Based on type annotations, some
arguments can be inferred from the function signature to pass data to the
original
add_argument()
method:
# example03.py
import clig
def recordperson(name: str, age: int, height: float):
print(locals())
clig.run(recordperson)
The types in the annotation may be used in the
add_argument()
method as type keyword
argument, when possible:
> python example03.py John 37 1.73
{'name': 'John', 'age': 37, 'height': 1.73}
And the type conversions are performed as usual
> python example03.py Mr John Doe
usage: recordperson [-h] name age height
recordperson: error: argument age: invalid int value: 'John'
Booleans
Booleans are transformed into arguments with
action of kind
"store_true" or "store_false" (depending on the default value).
# example04.py
import clig
def recordperson(name: str, employee: bool = False):
print(locals())
clig.run(recordperson)
> python example04.py -h
usage: recordperson [-h] [--employee] name
positional arguments:
name
options:
-h, --help show this help message and exit
--employee
> python example04.py --employee Leo
{'name': 'Leo', 'employee': True}
> python example04.py Ana
{'name': 'Ana', 'employee': False}
Required booleans
If no default is given to the boolean, a
required=True
keyword argument is used in the
add_argument()
method and a
BooleanOptionalAction
is used as action
keyword argument, adding support for a boolean complement action in the form
--no-option:
# example05.py
import clig
def recordperson(name: str, employee: bool):
print(locals())
clig.run(recordperson)
> python example05.py -h
usage: recordperson [-h] --employee | --no-employee name
positional arguments:
name
options:
-h, --help show this help message and exit
--employee, --no-employee
> python example05.py Ana
usage: recordperson [-h] --employee | --no-employee name
recordperson: error: the following arguments are required: --employee/--no-employee
Tuples, Lists and Sequences: nargs
The original nargs
keyword argument associates a different number of command-line arguments with a
single action. This is inferrend in types using tuple, list and Sequence.
Tuples
If the type is a tuple of specified length N, the argument automatically
uses nargs=N.
# example06.py
import clig
def main(name: tuple[str, str]):
print(locals())
clig.run(main)
> python example06.py -h
usage: main [-h] name name
positional arguments:
name
options:
-h, --help show this help message and exit
> python example06.py rocky yoco
{'name': ('rocky', 'yoco')}
> python example06.py rocky
usage: main [-h] name name
main: error: the following arguments are required: name
The argument can be positional (required, as above) or optional (with a default).
# example07.py
import clig
def main(name: tuple[str, str, str] = ("john", "mary", "jean")):
print(locals())
clig.run(main)
> python example07.py
{'name': ('john', 'mary', 'jean')}
> python example07.py --name yoco
usage: main [-h] [--name NAME NAME NAME]
main: error: argument --name: expected 3 arguments
> python example07.py --name yoco rocky sand
{'name': ('yoco', 'rocky', 'sand')}
List, Sequences and Tuples of any length
If the type is a generic Sequence, a list or a tuple of any length
(i.e., tuple[<type>, ...]), it uses
nargs="+" if it is
required (non default value) or
nargs="*" if it is
not required (has a default value).
# example08.py
import clig
def main(names: list[str]):
print(locals())
clig.run(main)
In this example, we have names using
nargs="+"
> python example08.py -h
usage: main [-h] names [names ...]
positional arguments:
names
options:
-h, --help show this help message and exit
> python example08.py chester philip
{'names': ['chester', 'philip']}
> python example08.py
usage: main [-h] names [names ...]
main: error: the following arguments are required: names
In the next example, we have names as optional argument, using
nargs="*"
# example09.py
import clig
def main(names: list[str] | None = None):
print(locals())
clig.run(main)
> python example09.py -h
usage: main [-h] [--names [NAMES ...]]
options:
-h, --help show this help message and exit
--names [NAMES ...]
> python example09.py --names katy buba
{'names': ['katy', 'buba']}
> python example09.py
{'names': None}
Literals and Enums: choices
If the type is a
Literal or a
Enum the argument
automatically uses
choices.
# example10.py
from typing import Literal
import clig
def main(name: str, move: Literal["rock", "paper", "scissors"]):
print(locals())
clig.run(main)
> python example10.py -h
usage: main [-h] name {rock,paper,scissors}
positional arguments:
name
{rock,paper,scissors}
options:
-h, --help show this help message and exit
As is expected in argparse,
an error message will be displayed if the argument was not one of the acceptable
values:
> python example10.py John knife
usage: main [-h] name {rock,paper,scissors}
main: error: argument move: invalid choice: 'knife' (choose from rock, paper, scissors)
> python example10.py Mary paper
{'name': 'Mary', 'move': 'paper'}
Passing Enums
In the command line, Enum should be passed by name, regardless of if it is a
number Enum or ar string Enum
# example11.py
from enum import Enum, StrEnum
import clig
class Color(Enum):
red = 1
blue = 2
yellow = 3
class Statistic(StrEnum):
minimun = "minimun"
mean = "mean"
maximum = "maximum"
def main(color: Color, statistic: Statistic):
print(locals())
clig.run(main)
> python example11.py -h
usage: main [-h] {red,blue,yellow} {minimun,mean,maximum}
positional arguments:
{red,blue,yellow}
{minimun,mean,maximum}
options:
-h, --help show this help message and exit
It is correctly passed to the function
> python example11.py red mean
{'color': <Color.red: 1>, 'statistic': <Statistic.mean: 'mean'>}
> python example11.py green
usage: main [-h] {red,blue,yellow} {minimun,mean,maximum}
main: error: argument color: invalid choice: 'green' (choose from red, blue, yellow)
Literal with Enum
You can even mix Enum and Literal, following the
Literal specification
# example12.py
from typing import Literal
from enum import Enum
import clig
class Color(Enum):
red = 1
blue = 2
yellow = 3
def main(color: Literal[Color.red, "green", "black"]):
print(locals())
clig.run(main)
> python example12.py red
{'color': <Color.red: 1>}
> python example12.py green
{'color': 'green'}
Variadic arguments (*args and **kwargs): Partial parsing
When the function has variadic arguments in the form *args or **kwargs, the
parse_known_args()
method will be used internally to gather unspecified arguments:
>>> import clig
>>> def variadics(foo: str, *args, **kwargs):
... print(locals())
...
>>> clig.run(variadics, "bar badger BAR spam --name adam --title mister".split())
{'foo': 'bar', 'args': ('badger', 'BAR', 'spam'), 'kwargs': {'name': 'adam', 'title': 'mister'}}
*args
For
arbitrary arguments in the form *args,
the unspecified arguments will be wrapped up in a tuple of strings, by default.
If there is a type annotation, the conversion is made in the whole tuple:
>>> import clig
>>> def variadicstyped(number: float, *integers: int):
... print(locals())
...
>>> clig.run(variadicstyped, ["36.7", "1", "2", "3", "4", "5"])
{'number': 36.7, 'integers': (1, 2, 3, 4, 5)}
**kwargs
For
arbitrary keyword arguments in the form **kwargs,
the unspecified arguments will be wrapped up in a dictionary of strings by
default. The keys of the dictionary are the names used with the option delimiter
in the command line (usually - or --). If there are more than one value for
each option, they are gathered in a list:
# example13.py
import clig
def foobar(name: str, **kwargs):
print(locals())
clig.run(foobar)
> python example13.py joseph --nickname joe --uncles jack jean adam
{'name': 'joseph', 'kwargs': {'nickname': 'joe', 'uncles': ['jack', 'jean', 'adam']}}
If there is a type annotation, the conversion is made in all elements of the dictionary
# example14.py
import clig
def foobartyped(name: str, **intergers: int):
print(locals())
clig.run(foobartyped)
> python example14.py joseph --age 23 --numbers 25 27 30
{'name': 'joseph', 'intergers': {'age': 23, 'numbers': [25, 27, 30]}}
> python example14.py joseph --age 23 --numbers jack jean adam
ValueError: invalid literal for int() with base 10: 'jack'
Error when passing flagged arguments to *args
The flag delimiters (usually - or --,
which can be changed)
are always interpreted as prefix for keyword arguments, raising the correct
error when not allowed:
# example15.py
import clig
def bazham(name: str, *uncles: str):
print(locals())
clig.run(bazham)
> python example15.py joseph jack john
{'name': 'joseph', 'uncles': ('jack', 'john')}
> python example15.py joseph --uncles jack john
TypeError: bazham() got an unexpected keyword argument 'uncles'
Argument specification
In some complex cases supported by
argparse, the arguments may
not be completely inferred by
clig.run()
on the function signature.
In theses cases, you can directly specificy the arguments parameters using the
Annotated
typing (or its clig's alias Arg) with its "metadata" created with the
data()
function.
The
data()
function accepts all possible arguments of the original
add_argument()
method:
name or flags
The
name_or_flags
parameter can be used to define additional flags for the arguments, like -f or
--foo:
# example16.py
from clig import Arg, data, run
def main(foobar: Arg[str, data("-f", "--foo")] = "baz"):
print(locals())
run(main)
> python example16.py -h
usage: main [-h] [-f FOOBAR]
options:
-h, --help show this help message and exit
-f FOOBAR, --foo FOOBAR
name or flags
can also be used to turn a positional argument (without default) into a
required flagged
argument (a required option):
# example17.py
from clig import Arg, data, run
def main(foo: Arg[str, data("-f")]):
print(locals())
run(main)
> python example17.py -h
usage: main [-h] -f FOO
options:
-h, --help show this help message and exit
-f FOO, --foo FOO
> python example17.py
usage: main [-h] -f FOO
main: error: the following arguments are required: -f/--foo
[!NOTE]
As you can see above,cligtries to create a long flag (--) for the argument when only short flags (-) are defined, but not when long flags are already defined. However, this behavior can be disabled.
Some options for the
name or flags
parameter
can also be set in the run() function.
nargs
Other cases of nargs
can be specified in the data() function.
The next example uses an optional argument with
nargs="?" and
const, which brings 3
different behaviors for the optional argument:
- value passed
- value not passed (sets default value)
- option passed without value (sets const value):
>>> from clig import Arg, data, run
...
>>> def main(foo: Arg[str, data(nargs="?", const="c")] = "d"):
... print(locals())
...
>>> run(main, ["--foo", "YY"])
{'foo': 'YY'}
>>> run(main, [])
{'foo': 'd'}
>>> run(main, ["--foo"])
{'foo': 'c'}
The next example makes optional a positional argument (not flagged), by using
nargs="?" and
default (which
would default to None):
>>> from clig import Arg, data, run
>>> def main(foo: Arg[str, data(nargs="?", default="d")]):
... print(locals())
...
>>> run(main, ["YY"])
{'foo': 'YY'}
>>> run(main, [])
{'foo': 'd'}
action
Other options for the
action parameter can
also be used in the data() function:
>>> from clig import Arg, data, run
>>> def append(foo: Arg[list[str], data(action="append")] = ["0"]):
... print(locals())
...
>>> def append_const(bar: Arg[list[int], data(action="append_const", const=42)] = [42]):
... print(locals())
...
>>> def extend(baz: Arg[list[float], data(action="extend")] = [0]):
... print(locals())
...
>>> def count(ham: Arg[int, data(action="count")] = 0):
... print(locals())
...
>>> run(append, "--foo 1 --foo 2".split())
{'foo': ['0', '1', '2']}
...
>>> run(append_const, "--bar --bar --bar --bar".split())
{'bar': [42, 42, 42, 42, 42]}
...
>>> run(extend, "--baz 25 --baz 50 65 75".split())
{'baz': [0, 25.0, 50.0, 65.0, 75.0]}
...
>>> run(count, "--ham --ham --ham".split())
{'ham': 3}
metavar
The parameter
metavar is used to
set alternative names in help messages to refer to arguments. By default, they
would be referend as just the argument name, if positional, and the argument
name uppercased, if optional.
# example18.py
from clig import Arg, data, run
def main(ham: Arg[str, data(metavar="YYY")], foo: Arg[str, data("-f", metavar="<foobar>")]):
print(locals())
run(main)
> python example18.py -h
usage: main [-h] -f <foobar> YYY
positional arguments:
YYY
options:
-h, --help show this help message and exit
-f <foobar>, --foo <foobar>
Some options for the
metavar argument
can also be set in the run() function.
help
It is more convenient to specify helps for arguments in the docstring.
However, you can define helps using the
data()
function in the same way as in the original method
add_argument().
Helps passed in the
data()
function takes precedence.
# example19.py
from clig import Arg, data, run
def mycommand(number: Arg[int, data(help="a different help for the number")]):
"""Description of the command
Args:
number: a number to compute
"""
pass
run(mycommand)
> python example19.py -h
usage: mycommand [-h] number
Description of the command
positional arguments:
number a different help for the number
options:
-h, --help show this help message and exit
Some options for the
help argument
can also be set in the run() function.
Argument groups
The
argparse
module has the features of
argument groups
and
mutually exclusive argument groups.
These features can be used in clig with 2 additional classes:
ArgumentGroup
and
MutuallyExclusiveGroup.
The object created with these classes can be used in the group parameter of
the
data()
function.
Each class accepts all the parameters of the original methods
add_argument_group()
and
add_mutually_exclusive_group().
# example20.py
from clig import Arg, data, run, ArgumentGroup
g = ArgumentGroup(title="Group of arguments", description="This is my group of arguments")
def main(foo: Arg[str, data(group=g)], bar: Arg[int, data(group=g)] = 42):
print(locals())
run(main)
> python example20.py -h
usage: main [-h] [--bar BAR] foo
options:
-h, --help show this help message and exit
Group of arguments:
This is my group of arguments
foo
--bar BAR
Remember that mutually exclusive arguments
must be optional
(either by using a flag in the
data
function, or by setting a deafult value):
# example21.py
from clig import Arg, data, run, MutuallyExclusiveGroup
g = MutuallyExclusiveGroup()
def main(foo: Arg[str, data("-f", group=g)], bar: Arg[int, data(group=g)] = 42):
print(locals())
run(main)
> python example21.py --foo rocky --bar 23
usage: main [-h] [-f FOO | --bar BAR]
main: error: argument --bar: not allowed with argument -f/--foo
Required mutually exclusive group
A
required
argument is accepted by the
MutuallyExclusiveGroup
in the same way it is done with the original method
add_mutually_exclusive_group()
(to indicate that at least one of the mutually exclusive arguments is required):
# example22.py
from clig import Arg, data, run, MutuallyExclusiveGroup
g = MutuallyExclusiveGroup(required=True)
def main(foo: Arg[str, data(group=g)] = "baz", bar: Arg[int, data(group=g)] = 42):
print(locals())
run(main)
> python example22.py -h
usage: main [-h] (--foo FOO | --bar BAR)
options:
-h, --help show this help message and exit
--foo FOO
--bar BAR
> python example22.py
usage: main [-h] (--foo FOO | --bar BAR)
main: error: one of the arguments --foo --bar is required
Mutually exclusive group added to an argument group
The
MutuallyExclusiveGroup
constructor class also accepts an additional
argument_group
parameter, because
a mutually exclusive group can be added to an argument group.
# example23.py
from clig import Arg, data, run, ArgumentGroup, MutuallyExclusiveGroup
ag = ArgumentGroup(title="Group of arguments", description="This is my group")
meg = MutuallyExclusiveGroup(argument_group=ag)
def main(
foo: Arg[str, data(group=meg)] = "baz",
bar: Arg[int, data(group=meg)] = 42,
):
print(locals())
run(main)
> python example23.py -h
usage: main [-h] [--foo FOO | --bar BAR]
options:
-h, --help show this help message and exit
Group of arguments:
This is my group
--foo FOO
--bar BAR
However, you can define just the
MutuallyExclusiveGroup
object passing the parameters of
ArgumentGroup
to the constructor of the former class, which supports them:
# example24.py
from clig import Arg, data, run, MutuallyExclusiveGroup
g = MutuallyExclusiveGroup(
title="Group of arguments",
description="This is my exclusive group of arguments",
)
def main(
foo: Arg[str, data("-f", group=g)],
bar: Arg[int, data("-b", group=g)],
):
print(locals())
run(main)
> python example24.py -h
usage: main [-h] [-f FOO | -b BAR]
options:
-h, --help show this help message and exit
Group of arguments:
This is my exclusive group of arguments
-f FOO, --foo FOO
-b BAR, --bar BAR
Using the walrus operator (:=)
You can do argument group definition all in one single line (in the function
declaration) by using the
walrus operator
(:=):
# example25.py
from clig import Arg, data, run, MutuallyExclusiveGroup
def main(
foo: Arg[str, data(group=(g := MutuallyExclusiveGroup(title="My group")))] = "baz",
bar: Arg[int, data(group=g)] = 42,
):
print(locals())
run(main)
> python example25.py -h
usage: main [-h] [--foo FOO | --bar BAR]
options:
-h, --help show this help message and exit
My group:
--foo FOO
--bar BAR
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