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AutoConfig

A python utility for reading/writing custom YAML configuration files

Requirements

  • pyyaml
  • Python 3.6+ (not tested with earlier versions)

Installation

From within the AutoConfig folder:

pip install .

To uninstall:

pip uninstall AutoConfig

Usage

> YAML file formatting (see included example.yaml)

  • All config info exists as key:value pairs, which can be nested using indentation
  • Recognizes:
    • floats/ints
    • lists of values: [0.1, -1.1, 3] etc.
    • scientific notation: 1.1e-5
    • None: specified as null
    • Setting placeholders for later update: norm: ${norm} (see .update_reuse)
    • booleans
    • Everything is a string otherwise
  • Python comments are ignored: # like this

> args_from_YAML

The main class for reading/writing/printing from YAML config files

Configuration:

path | str

The path to the YAML file

subset | iterable of str, default=None:

An optional iterable of keys within the file to read, ignoring others

verbose | bool, default=False

Provides some info about the config being used

Functions

.reset(subset=["main"])

Re-loads the config from the originally provided path, if available

subset(s) can optionally be specified

.save_to_yaml(path, mode='w', exclude=["subset"])

Writes the current state of the class and its data to a yaml file

Optionally exclude subsets

.update_reuse(st_str="${", en_str="}", ignore="???", max_depth=10):

By default, any config items with the format "${name}" will be filled using a higher-level instance of "name"

For example; if "seed: 0" and "subconfig.seed: ${seed}" then it becomes "subconfig.seed: 0"

Additionally, any config items specified with the ignore value will not be propagated.

For example; if "seed: ???" and "subconfig.seed: ${seed}" then it remains "subconfig.seed: ${seed}"

Setting/Getting

  • Any config values (including nested) can be accessed via the format class_instance.key1.key2.key3
  • The class functions as an iterator (__iter__), yielding any keys
  • .pop(key) removes a given key (if available) and returns its matching value
  • Supports setting values via class_inst["key"] = value, including nested values class_inst["key"]["key2"]["key3"] = value
  • Supports getting values via class_inst["key"], including nested values class_inst["key"]["key2"]["key3"]
  • .get(keys) takes an iterable of keys and returns the value at the end of the key chain, if available
  • .set(keys) takes an iterable of keys and sets the value at the end of the key chain, if available
  • .get_dict() returns a dictionary representation of the current configuration
  • .print() uses DictionaryPrint to create a clean print of the data

Usage Example:

from AutoConfig import args_from_YAML

A = args_from_YAML(<config file path>, verbose=True)
A.update_reuse()

print(A.STE_cfg.noise_penalty)
print(A["DAAC_cfg"]["clip_param"])

A.print()

Result:

AutoConfig using: /home/user/Desktop/example.yaml, subset: None

0.001
0.2

config_path: /home/user/Desktop/example.yaml
______ seed: 0
_ save_path: /home/user/Desktop/Results/
____ device: cpu
__ data_dir: /home/user/Desktop/DataSets/
window_size: 128
______ mode: debug
______ norm: None
__ ENV_info:
           > __ input_dim: None
           > __ state_dim: None
           > _ action_dim: None
           > action_space: None
           > __ obs_shape: None
___ STE_cfg:
           > _________ seed: 0
           > _________ mode: debug
           > _________ norm: None
           > ____ save_path: /home/user/Desktop/Results/
           > __ window_size: 128
           > ___ stats_path: None
           > __________ kwd: None
           > _____ max_loss: None
           > _______ repeat: None
           >  noise_penalty: 0.001
           > data_divisions: [0.9, 0.1]
           > __ action_mode: soft
           > ______ deadlim: [0.1, 0.1]
__ DAAC_cfg:
           > ____________ seed: 0
           > __________ device: cpu
           > ________ env_name: STEnv
           > ______________ lr: 0.0005
           > _____________ eps: 1e-05
           > ___________ alpha: 0.99
           > ___________ gamma: 0.999
           > ______ gae_lambda: 0.95
           > ____ entropy_coef: 0.01
           > _ value_loss_coef: 0.5
           > ___ max_grad_norm: 0.5
           > ___ num_processes: 16
           > _______ num_steps: 256
           > _______ ppo_epoch: 1
           > __ num_mini_batch: 8
           > ______ clip_param: 0.2
           > ____ log_interval: 10
           > ___ num_env_steps: 2500
           > ____________ algo: idaac
           > _____ hidden_size: 256
           > _________ log_dir: /home/user/Desktop/Results/
           > _______ save_path: /home/user/Desktop/Results/
           > _____ value_epoch: 9
           > ______ value_freq: 1
           > ___ adv_loss_coef: 0.25
           > use_nonlinear_clf: False
           > _ clf_hidden_size: 4

> reassign(target, source)

A simple function for copying key:value attributes from one object to another

Useful for loading your config into a class without passing everything as kwargs

Example Usage:

from AutoConfig import reassign

my_class = dummy_class()

A = args_from_YAML(path)
print(A.save_path) # exists

print(my_class.save_path) # does not exist

reassign(my_class, A) # copy config info into "my_class"
print(my_class.save_path) # exists