Very opinionated configuration loading package for Python projects
Project description
Confuk
This is yet another package for managing configuration files in Python projects.
It exposes one function that lets you provide a path to a TOML/YAML/JSON configuration file. It parses the config file into a dictionary by default. If a config class is provided when parsing, the class instance will be created using a dictionary of keyword arguments coming from the original TOML/YAML/JSON file.
In human words: I made this package so that I don't have to explicilty load, parse and return a class instance every single time I have something to do with a configuration file:
from confuk import parse_config
from pathlib import Path
from somewhere import ConfigClass
cfg_dict = parse_config(Path("some.toml")) # returns a dictionary
cfg_obj = parse_config(Path("some.toml"), ConfigClass) # returns an instance of `ConfigClass`
[!tip]
confuk
also supports a number of output configuration styles out-of-the-box, includingomegaconf
, Pydantic andEasyDict
.
Installation
pip install confuk
Or:
poetry add confuk
Building from source
You can build the package using Poetry:
- Clone this repo.
- Run
poetry build
. - Grab the installable wheel from the
dist
folder and install it withpip
or add the package as a local dependency of another project.
Special features
Config output formats
EasyDict
If you really hate referring to dictionary keys and you do not intend to create a custom configuration class for your config, you can parse the file to an EasyDict
:
cfg_edict = parse_config(Path("some.toml"), "attr")
Now, if the key something
exists in the configuration file, you can simply refer to it using an attribute:
cfg_edict.something
OmegaConf
OmegaConf is one of the most complete configuration systems for Python applications. If you want to leverage its features while still working with confuk
as a front-end, you can simply parse the configuration into an instance of omegaconf.DictConfig
by doing the following:
cfg = parse_config(Path("some.toml"), "omega")
Pydantic
If you're a fan of Pydantic with custom config classes for automatic validation, just use any class that inherits from BaseModel
:
from confuk import parse_config
from pathlib import Path
from pydantic import BaseModel
class Metrics(BaseModel):
psnr: float
ssim: float
cfg_dict = parse_config(Path("some.toml"), Metrics) # returns a dictionary
All currently supported formats
Format | cfg_class argument |
---|---|
dict |
"d" / None |
EasyDict |
"ed" / "edict" / "attr" |
OmegaConf |
"o" / "omega" / "omegaconf" |
pydantic |
BaseModel class |
custom |
any class supporting **kwargs in the constructor |
Imports
Because keeping hundreds of config files can become tedious, especially when there is shared values between them, you might want to consider using the imports
functionality.
Say you have a TOML file from which you want to inherit values:
[something]
value = 1
another_value = 2
[something_else]
value = 3
You can "import" it using a preamble:
[pre]
imports = [
"${this_dir}/test_imported.toml",
]
[something]
value = 69
[!note] Older versions of
confuk
used the$this_dir
syntax instead. This will be supported going into the future but it won't work with variable interpolation (expect it to only work for the special interpolation markers such as$this_dir
and$cwd
).
This is equivalent to specifying a config like:
[something]
value = 69
another_value = 2
[something_else]
value = 3
Note that you can use several special interpolation markers to specify paths in the import section:
${this_dir}
-> points to a directory relative to the configuration file that contains theimport
section${cwd}
-> points to the current working directory${this_filename}
-> config filename (with extension)${this_filename_stem}
-> filename without the extension (stem)
[!warning] The preamble will be removed after it's processed. It's there only to control how
confuk
should process the loaded configuration files and it's dropped afterwards. Do not put any meaningful configuration into your preamble, except forconfuk
's control elements.
What about inheriting selected values?
Unsupported. And I do not plan to add support for cherrypicking values from other configs. It makes things way messier in my opinion, as it becomes way harder to reason about the flow of variables.
What about variable interpolation?
This is supported with the syntax that OmegaConf uses, e.g. path = "${some.root.path}/file.txt"
will pick up the path
variable from some.root
config section. The interpolation markers that I mentioned in the Imports
section should also work anywhere else within the config, so you can use your ${this_filename_stem}
to refer to config names within the config itself. One use-case is when you want to have subdirectories in a results
directory, where you would silo away the results from different configs:
results_dir = "results/${this_filename_stem}"
Assumming that you have 3 configs for your experiments: ex1
, ex2
and ex3
, you could instead put results_dir
in a parent config to all those:
# to_import.toml:
results_dir = "results/${this_filename_stem}"
# ex1
[pre]
imports = ["${this_dir}/to_import.toml"]
a_variable_that_diverges_across_configs = 69
# ex2
[pre]
imports = ["${this_dir}/to_import.toml"]
a_variable_that_diverges_across_configs = 420
# ex3
[pre]
imports = ["${this_dir}/to_import.toml"]
a_variable_that_diverges_across_configs = 42
[!note] We are using
omegaconf
for all other interpolation tasks under the hood since they already have a great parser for this and there's no use duplicating work.
What about deeply nested configs?
If you like the deeply nested folder-file structure for your configs then Hydra might be more for you. I've used it before and it's very good but I personally find the design choice of creating directory structures for configs quite tedious.
confuk
strives to be flatter: you import another config file in the preamble section and you have a choice of what to override. This makes it more comfortable to use when you have one default.toml
config file for something and then create a bunch of configurations overriding certain values. This is useful for experiments in the AI/ML space, where I'm spending most of my time now.
You are of course free to structure your files as you please but don't expect a feature similar to Hydra's defaults
in confuk
– I do indeed use Hydra for applications which require such a system!
Command-line overrides
One of the most fantastic features I've found when using Hydra was the ability to override values from the config file on the command line. This is convenient when you want to quickly test some changes to your configuration without going through the trouble of creating a new config file.
So I concluded it would be fun to implement it in confuk
in a similar fashion. Here's how it works:
import confuk
@confuk.main(config=Path(__file__).parent / "test.toml", config_format="o", verbose=False)
def main(cfg, *args):
console = Console()
console.print(cfg)
return cfg
This decorator behaves similarly to @hydra.main
decorator and it creates a minimal argument parser for your application entrypoint under the hood.
Now, when running the app, you can specify any value overrides on the command line. For example if your config looks like this:
[my]
mother = 1
[your.dad]
father = 1
And you run your CLI app with the argument your.dad.father=3
, you will override the pertinent value from 1
to 3
.
[!tip] The underlying argument parser also contains a
--config
option. You can use it to switch to a different config path on the command line, without a need to rely on the default one that has been set in the decorator.
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