minydra 0.1.3

Easily parse arbitrary arguments from the command line without dependencies

minydra 🦎

Minimal Python command-line parser inspired by Facebook's Hydra + dot-accessible dictionary.

Easily parse arbitrary arguments from the command line without dependencies:

pip install minydra

minydra is tested on Python 3.7, 3.8 and 3.9.

Usage

examples/parser.py

from minydra.parser import Parser

if __name__ == "__main__":
    parser = Parser(
        verbose=0, # print received args
        allow_overwrites=False, # allow repeating args in the command-line
        warn_overwrites=True, # warn repeating args if they are allowed
        parse_env=True, # get environment variable
        warn_env=True, # warn if an environment variable is specified but not found
    )
    args = parser.args.pretty_print().resolve().pretty_print() # notice .resolve() transforms dotted.keys into nested dicts

examples/resolved_args.py

from minydra import resolved_args

if __name__ == "__main__":
    args = resolved_args()
    args.pretty_print()

examples/demo.py examples/demo.json

from minydra import resolved_args, MinyDict

if __name__ == "__main__":
    # parse arbitrary args in 1 line
    args = resolved_args()

    # override default conf
    if args.default:
        args = MinyDict.from_json(args.default).update(args)

    # print the args in a nice orderly fashion
    args.pretty_print()

    # access args with dot/attribute access
    print(f'Using project "{args.log.project}" in {args.log.outdir}')

examples/decorator.py

import minydra
from minydra.dict import MinyDict

@minydra.parse_args(verbose=0, allow_overwrites=False) # Parser's init args work here
def main(args: MinyDict) -> None:
    args.resolve().pretty_print()


if __name__ == "__main__":
    main()

Parsing

• Simple strings are parsed to float and int automatically.
• A single keyword will be interpreted as a positive flag.
• A single keyword starting with - will be interpreted as a negative flag.
• If parse_env is True, environment variables are evaluated.

$ python decorator.py outdir=$HOME/project save -log learning_rate=1e-4 batch_size=64
╭───────────────────────────────────────────╮
│ batch_size    : 64                        │
│ learning_rate : 0.0001                    │
│ log           : False                     │
│ outdir        : /Users/victor/project     │
│ save          : True                      │
╰───────────────────────────────────────────╯

• dotted keys will be resolved to nested dictionary keys:

$ python decorator.py server.conf.port=8000
╭─────────────────────╮
│ server              │
│   conf              │
│     port : 8000     │
╰─────────────────────╯

• Using ast.literal_eval(value), minydra will try and parse more complex values for arguments as lists or dicts. Those should be specified as strings:

$ python examples/decorator.py layers="[1, 2, 3]" norms="{'conv': 'batch', 'epsilon': 1e-3}"
╭──────────────────────────────────────────────────╮
│ layers : [1, 2, 3]                               │
│ norms  : {'conv': 'batch', 'epsilon': 0.001}     │
╰──────────────────────────────────────────────────╯

Forcing types

Adding ___<type> to a key will force this type to the value. Notice how 01 is parsed to an integer 1 but 04 is parsed to a string (as specified) "04", and hello is parsed to a list, not kept as a string

$ python examples/decorator.py n_jobs___str=04 job=01 chips___list=hello 
╭────────────────────────────────────────╮
│ chips  : ['h', 'e', 'l', 'l', 'o']     │
│ job    : 1                             │
│ n_jobs : 04                            │
╰────────────────────────────────────────╯

Known types are defined in Parser.known_types and the separator (___) in Parser.type_separator

In [1]: from minydra import Parser

In [2]: Parser.known_types
Out[2]: {'bool', 'dict', 'float', 'int', 'list', 'set', 'str'}

MinyDict

Minydra's args are a custom lightweight wrapper around native dict which allows for dot access (args.key), resolving dotted keys into nested dicts and pretty printing sorted keys in a box with nested dicts indented. If a key does not exist, it will not fail, rather return None (as dict.get(key, None)).

a MinyDict inherits from dict so usual methods work .keys(), .items() etc.

In [1]: from minydra.dict import MinyDict

In [2]: args = MinyDict({"foo": "bar", "yes.no.maybe": "idontknow"}).pretty_print(); args
╭──────────────────────────────╮
│ foo          : bar           │
│ yes.no.maybe : idontknow     │
╰──────────────────────────────╯
Out[2]: {'foo': 'bar', 'yes.no.maybe': 'idontknow'}

In [3]: args.resolve().pretty_print(); args
╭───────────────────────────╮
│ foo : bar                 │
│ yes                       │
│   no                      │
│     maybe : idontknow     │
╰───────────────────────────╯
Out[3]: {'foo': 'bar', 'yes': {'no': {'maybe': 'idontknow'}}}

In [4]: args.yes.no.maybe
Out[4]: "idontknow"

In [5]: "foo" in args
Out[5]: True

In [6]: "rick" in args
Out[6]: False

In [7]: args.morty is None
Out[7]: True

In [8]: args.items()
Out[8]: dict_items([('foo', 'bar'), ('yes', {'no': {'maybe': 'idontknow'}})])

Dumping/Loading

You can save and read MinyDict to/from disk in two formats: json and pickle.

Both to_pickle and to_json have 3 arguments:

1. file_path as a str or pathlib.Path which is resolved:
   1. expand env variable ($MYDIR for instance)
   2. expand user (~)
   3. make absolute
2. return_path which defaults to True. If True to_json and to_pickle return the path of the created object
3. allow_overwrites which defaults to True. If False and path exists, a FileExistsError will be raised. Otherwise creates/overwrites the file at file_path
4. verbose which defaults to 0. If >0 prints the path of the created object

json

Warning: the json standard does not accept ints as keys in dictionaries so {3: 2} would be dumped -- and therefore loaded -- as {"3": 2}.

In [1]: from minydra.dict import MinyDict

In [2]: args = MinyDict({"foo": "bar", "yes.no.maybe": "idontknow"}).resolve(); args
Out[2]: {'foo': 'bar', 'yes': {'no': {'maybe': 'idontknow'}}}

In [3]: args.to_json("./opts.json")

In [4]: args.to_json("./opts.json", verbose=1)
Json dumped to: /Users/victor/Documents/Github/vict0rsch/minydra/opts.json

In [5]: MinyDict.from_json("opts.json")
Out[5]: {'foo': 'bar', 'yes': {'no': {'maybe': 'idontknow'}}}

pickle

In [1]: from minydra.dict import MinyDict

In [2]: args = MinyDict({"foo": "bar", "yes.no.maybe": "idontknow"}).resolve()

In [3]: print(args)
{'foo': 'bar', 'yes': {'no': {'maybe': 'idontknow'}}}

In [4]: assert args == MinyDict.from_pickle(args.to_pickle("opts.pkl"))

examples/dumps.py

python examples/dumps.py path="./myargs.pkl" format=pickle cleanup

╭────────────────────────────╮
│ cleanup : True             │
│ format  : pickle           │
│ path    : ./myargs.pkl     │
╰────────────────────────────╯
Dumped args to /Users/victor/Documents/Github/vict0rsch/minydra/myargs.pkl
Cleaning up

pretty_print

Prints the Minydict in a box, with dicts properly indented. A few arguments:

1. indents, which defaults to 2: the amount of indentation for nested dictionaries
2. sort_keys, which defaults to True: whether or not to alphabetically sort the keys before printing

to_dict

To produce a native Python dict, use args.to_dict()

Protected attributes

MinyDict's methods (including the dict class's) are protected, they are read-only and you cannot therefore set attributes with there names, like args.get = 2. If you do need to have a get argument, you can access it through items: args["get"] = 2.

Try with examples/protected.py:

python examples/protected.py server.conf.port=8000 get=3   
╭─────────────────────╮
│ get    : 3          │
│ server              │
│   conf              │
│     port : 8000     │
╰─────────────────────╯
<built-in method get of MinyDict object at 0x100ccd4a0>
3
dict_items([('get', 3), ('server', {'conf': {'port': 8000}})])
{'conf': {'port': 8000}}