The nicest way to develop a command-line interface
Project description
Coleo
Coleo is a minimum-effort way to create a command-line interface in Python.
- Declare options where they are used.
- Scale easily to extensive CLIs with dozens of subcommands and options.
Basic usage
First, define a command line interface as follows:
from coleo import Option, auto_cli, default
@auto_cli
def main():
# The greeting
greeting: Option = default("Hello")
# The name to greet
name: Option = default("you")
return f"{greeting}, {name}!"
Then you may run it like this on the command line:
$ python hello.py
Hello, you!
$ python hello.py --name Luke
Hello, Luke!
$ python hello.py --name Luke --greeting "Happy birthday"
Happy birthday, Luke!
$ python hello.py -h
usage: hello.py [-h] [--greeting VALUE] [--name VALUE]
optional arguments:
-h, --help show this help message and exit
--greeting VALUE The greeting
--name VALUE The name to greet
- Any variable annotated with
Option
will become an option. - You can provide a default value with
default(value)
, although you don't have to, if the argument is required. - If there is a comment above the variable, it will be used as documentation for the option.
Option types
By default, all arguments are interpreted as strings, but you can easily give a different type to an argument:
@auto_cli
def main():
# This argument will be converted to an int
x: Option & int
# This argument will be converted to a float
y: Option & float
return x + y
Boolean flags
If the type is bool, the option will take no argument, for example:
@auto_cli
def main():
flag: Option & bool = default(False)
return "yes!" if flag else "no!"
Use it like this:
$ python script.py --flag
yes!
$ python script.py
no!
You can also negate the flag, meaning that you want to provide an option that will store False in the variable instead of True. For example:
@auto_cli
def main():
# [negate]
flag: Option & bool = default(True)
return "yes!" if flag else "no!"
By default, the above will create a flag called --no-<optname>
:
$ python script.py
yes!
$ python script.py --no-flag
no!
You can write [negate: --xyz -n]
if you want the option to be --xyz
or -n
. This overrides the default --no-flag
option.
Note that using [negate]
will remove --flag
, because we assume that it is True by default and there is therefore no need for this option.
If you wish, you can have both options that set the flag to True and others that set the flag to False, using [false-options]
. You can optionally document these options with [false-options-doc]
(if not provided, Coleo will use a sensible default):
@auto_cli
def main():
# Set the flag to True
# [options: -y]
# [false-options: -n]
# [false-options-doc: Set the flag to False]
flag: Option & bool = default(None)
return flag
$ python script.py
None
$ python script.py -y
True
$ python script.py -n
False
Files
Use coleo.FileType
(or argparse.FileType
, it's the same thing) to open a file to read from or to write to:
@auto_cli
def main():
grocery_list: Option & coleo.FileType("r")
with grocery_list as f:
for food in f.readlines():
print(f"Gotta buy some {food}")
Config
You can manipulate configuration files with coleo.config
or coleo.ConfigFile
:
@auto_cli
def main():
# ConfigFile lets you read or write a configuration file
book: Option & ConfigFile
contents = book.read()
contents["xyz"] = "abc"
book.write(contents)
# config will read the file for you or parse the argument as JSON
magazine: Option & config
print(magazine)
Use it simply like this:
$ python librarian.py --book alice.json --magazine vogue.json
$ python librarian.py --book history.yaml --magazine gamez.toml
$ python librarian.py --book physics.json --magazine '{"a": 1, "b": 2}'
# etc
Supported extensions are json
, yaml
and toml
(the latter two require installing the pyyaml
or toml
packages).
Other
Any function can be used as a "type" for an argument. So for example, if you want to be able to provide lists and dictionaries on the command line you can simply use json.loads
(although coleo.config
is usually better, because it can also read files, in various formats):
@auto_cli
def main():
obj: Option & json.loads
return type(obj).__name__
$ python json.py --obj 1
int
$ python json.py --obj '"hello"'
str
$ python json.py --obj '{"a": 1, "b": 2}'
dict
If you're feeling super feisty and care nothing about safety, you can even use eval
:
@auto_cli
def main():
obj: Option & eval
return type(obj).__name__
$ python eval.py --obj "1 + 2"
int
$ python eval.py --obj "lambda x: x + 1"
function
Customization
Using comments of the form # [<instruction>: <args ...>]
you can customize the option parser:
@auto_cli
def main():
# This argument can be given as either --greeting or -g
# [alias: -g]
greeting: Option = default("Hello")
# This argument is positional
# [positional]
name: Option = default("you")
# This argument can only be given as -n
# [options: -n]
ntimes: Option & int = default(1)
for i in range(ntimes):
print(f"{greeting}, {name}!")
The above would be used like this:
$ python hello.py Alice -g Greetings -n 2
Greetings, Alice!
Greetings, Alice!
The following customizations are available:
[alias: ...]
defines one or several options that are aliases for the main one. Options are separated by spaces, commas or semicolons.[options: ...]
defines one or several options for this argument, which override the default one. Options are separated by spaces, commas or semicolons.[positional]
defines one positional argument.[positional: n]
: n positional arguments (a list is returned).[positional: ?]
: one optional positional argument[positional: *]
: zero or more positional arguments[positional: +]
: one or more positional arguments
[remainder]
represents all arguments that are not matched by the argument parser[nargs: n]
declares that the option takes n arguments[nargs: ?]
: one optional argument[nargs: *]
: zero or more arguments[nargs: +]
: one or more arguments[nargs: **]
or[nargs: --]
: all remaining arguments, including --args
[action: <action>]
customizes the action to perform[action: append]
lets you use an option multiple times, accumulating the results in a list (e.g.python app.py -a 1 -a 2 -a 3
, would put[1, 2, 3]
ina
)
[metavar: varname]
changes the variable name right after the option in the help string, e.g.--opt METAVAR
[group: groupname]
puts the option in a named group. Options in the same group will appear together in the help.- For bool options only:
[negate: ...]
changes the option so that it sets the variable to False instead of True when they are given. Space/comma aliases may be provided for the option, otherwise the flag will be named--no-<optname>
.[false-options: ]
provide a list of options that set the flag to False.[false-options-doc: ]
provide a documentation for the options given using the previous statement.
Subcommands
You can create an interface with a hierarchy of subcommands by decorating a class with auto_cli
:
@auto_cli
class main:
class calc:
def add():
x: Option & int
y: Option & int
return x + y
def mul():
x: Option & int
y: Option & int
return x * y
def pow():
base: Option & int
exponent: Option & int
return base ** exponent
def greet():
greeting: Option = default("Hello")
name: Option = default("you")
return f"{greeting}, {name}!"
The class only holds structure and will never be instantiated, so don't add self
to the argument lists for these functions.
Then you may use it like this:
$ python multi.py greet --name Alice --greeting Hi
Hi, Alice!
$ python multi.py calc add --x=3 --y=8
11
Sharing arguments
It is possible to share behavior and arguments between subcommands, or to split complex functionality into multiple pieces. For example, maybe multiple subcommands in your application require an API key, which can either be given on the command line or can be read from a file. This is how you would share this behavior across all subcommands:
from coleo import Option, auto_cli, config, default, tooled
@tooled
def apikey():
# The API key to use
key: Option = default(None)
if key is None:
# If no key parameter is given on the command line, try to read it from
# some standard location.
key = config("~/.config/myapp/config.json")["key"]
return key
@auto_cli
class main:
def search():
interface = Application(apikey())
query: Option
return interface.search(query)
def install():
interface = Application(apikey())
package: Option
return interface.install(package)
If a function is decorated with @tooled
and is called from one of the main functions (or from another tooled function), Coleo will search for arguments in that function too. Thus any subcommand that calls apikey()
will gain a --key
option.
In addition to this, you can "share" arguments by defining the same argument with the same type in multiple functions. Coleo will set all of them to the same value.
For example, in the example above you could easily let the user specify the path to the file that contains the key, simply by replacing
key = config("~/.config/myapp/config.json")["key"]
# ==>
config_path: Option = default("~/.config/myapp/config.json")
key = config(config_path)["key"]
And that config_path
argument could, of course, be declared in any other function that needs to read some configuration value.
run_cli
from coleo import Option, auto_cli
@auto_cli
def main():
x: Option
return x
Is equivalent to:
from coleo import Option, run_cli, tooled
@tooled
def main():
x: Option
return x
result = run_cli(main)
if result is not None:
print(result)
Non-CLI usage
It is possible to set arguments without auto_cli
using setvars
:
from coleo import Option, setvars, tooled
@tooled
def greet():
greeting: Option = default("Hello")
name: Option = default("you")
return f"{greeting} {name}!"
with setvars(greeting="Hi", name="Bob"):
assert greet() == "Hi bob!"
Note:
- With
setvars
, you must decorate the function with@tooled
(this is somethingauto_cli
does on your behalf). setvars
entirely bypasses the option parsing and the type annotations will not be used to wrap these values. In other words, if a variable is annotatedOption & int
and you provide the value "1", it will remain a string.
Using with Ptera
Coleo is based on Ptera and all of Ptera's functionality is de facto available on functions marked as @tooled
. For example, using the example above:
# Set the variables in the greet function -- it's a bit like making an object
hibob = greet.new(greeting="Hi", name="Bob")
assert hibob() == "Hi Bob!"
# Same as above but this would also change greeting/name in any other function
# that is called by greet, and so on recursively (a bit like dynamic scoping)
hibob = greet.tweaking({"greeting": "Hi", "name": "Bob"})
assert hibob() == "Hi Bob!"
# More complex behavior
from ptera import overlay
with overlay.tweaking({
"greet(greeting='Bonjour') > name": "Toto"
}):
assert greet() == "Hello you!"
assert greet.new(greeting="Hi")() == "Hi you!"
assert greet.new(greeting="Bonjour")() == "Bonjour toto!"
Read the documentation for Ptera for more information. Note that Ptera is not limited to variables tagged Option
, it can manipulate any variable in a tooled function.
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