A tiny library to support tunable parameters (think: configuration values) as they often occur in scientific analyses. A main aspect differing from many other config approaches is, that the tunables are defined as classes where needed throughout the source, with default value, type, optional documentation etc., which makes later access fast, IDE-supported (code completion) and prevents running it with "missing defaults" or misspelled keys leading to runtime errors.
Theoretically, all Python types instantiable from strings are supported, it is however discouraged to use anything but
{bool, int, float, str, bytes}
for portability reasons.
There are some more features and concepts, which will hopefully be documented correctly in the future.
Example test.py:
import argparse
from tunable import Tunable, TunableManager
# tunable values are just defined as classes
# inheriting from Tunable, their documentation
# being normal inline documentation
# their type is derived from their default value
class MyValue(Tunable):
"""An important tunable."""
default = 42.0
def main():
# TunableManager provides some argparser-actions
# to allow users to interact with tunables
p = argparse.ArgumentParser()
TunableManager.register_argparser(p)
p.parse_args()
# Access to the value is straightforward:
print(MyValue.value)
# will be accessed once dynamically with checks,
# afterwards as a simple lookup
if __name__ == '__main__':
main()
Without arguments:
> python test.py
42.0
Functionality can automatically be registered with argparser.
> python test.py --help
usage: test.py [-h] [--tunables-show] [-t TUNABLE]
[--tunables-load TUNABLES_LOAD] [--tunables-save TUNABLES_SAVE]
optional arguments:
-h, --help show this help message and exit
--tunables-show
-t TUNABLE, --tunable TUNABLE
--tunables-load TUNABLES_LOAD
--tunables-save TUNABLES_SAVE
Show set tunables:
> python test.py --tunables-show
### Tunables ###
# An important tunable.
# type: float
MyValue=42.0
Changing a tunable via command line: (See how int(21) was upcasted to float)
> python test.py -t MyValue=21
21.0
Tunables can be saved/loaded from files, currently supported are key=value style config files, JSON, DER, YAML or XML.
To help reproducibility, a hash of all tunables currently set can be generated:
print(TunableManager.get_hash())
VERSION:1:SHA256:3aHPIn6bRgA15+dNRPNhltMA1hibYMcs7dnUwqVjg0s=
Cryptographic hashing is based upon the SHA-256 hash of a canonicalized DER based serialization of the tunables.
Warning, this library is beta software, whose interface is subject to change without notice!
No guarantees yet on binary formats, hash stability or such!
MIT