pyaconf 0.7.1

Yet another config library that is built around python dictionary and supports dynamic python, json, yaml, and ini formats with inheritance with Jinji2 templates

pyaconf - yet another config library built around python dictionary

Pyaconf is a config library that is built around python dictionary and supports dynamic python, json, yaml, and ini formats with inheritance. It features:

Features

• 4 formats (pyaconf [python], yaml, json, ini) that can be layered on top of each other,
• dynamic pyaconf (python) format,
• include feature that can layer combine the 4 formats hierarchically,
• “merge” capability that allows to override values by the topmost layer,
• jinja2 template substitution capability that can be injected at various layers of override and dictionary hierarchies,
• simple 3 function (load, merge, and dump) Python API, and
• command line utility that allows us to use all these features from the command line

Notes

• All configs are json compatible dicts.
• Supports layered configs (inheritance) via __include__ dict entry, for example, the following yaml config would read the dictionary defined from config boo.json and then will update it with user and password from this config:

__include__: boo.json
user: romeo
password: romeoalpha

• Includes may be used at any level and apply only to its layer.
• Simple API: load, dump, and for more advanced use merge.
• Supports dynamic configs written in Python .pyaconf, for example:

import os
def config():
   return dict(
      __include__ = ["secret.yml"],
      user = "romeo", 
      password = os.environ['PASSWORD'],
      database = dict(
         __include__ = "db.ini",
      ),
   )

• Allows to output configs in .json and .yaml. Provides two shell scripts.
• Supports .ini input format as understood by python's configparser.
• Supports Jinji2 templates, you just need to add .j2 or .jinji2 extension to your config file and it will be processed by Jinji2. For example:

user: {{ username }}
password = {{ password }}

• The dictionary that contains includes serves as a context for these includes. For template includes, the dictionary is passed as a context to the template processing. For non-template includes, the dictionary merges with the include. When all includes processed this way, they all merge together.

__include__: [a.yaml.j2, b.yaml]
x: 1
y: 2

• Another example with template:

# common.yaml.j2
host: local
user: {{ username }}
password: {{ password }}
credentials: [{{ password }}, {{username}}]

# devel.yaml
__include__: common.yaml.j2
username: Donald
password: Trump
office: 113D

# pyaconf_render -f json devel.yaml
{
  "credentials": [
     "Trump",
     "Donald"
  ],
  "host": "local",
  "password": "Trump",
  "user": "Donald"
}

API

load

def load(src, *, format='auto', path=None, context={}):
   """ loads a dict that may include special keyword '__include__' at multiple levels,
   and resolves these includes and returns a dict without includes. It can also read the input dict from a file
   src -- dict|Mapping, FILE|io.StringIO(s), pathlib.Path|str
   format -- 'auto' | 'pyaconf' | 'json' | 'yaml' | 'ini'
   path -- is used only when src doesn't contain path info, it is used for error messages and resolve relative include paths
   context -- is a dict that is used as context for template rendering if src is a template
   """

dump

def dump(x, dst=sys.stdout, *, format='auto'):
   """ Dumps resolved (without includes) config in json or yaml format. It doesn't preserve comments either. 
   x -- dict|Mapping
   dst -- FILE|io.StringIO(s), pathlib.Path|str
   format -- 'auto' | 'json' | 'yaml'
   """

merge

def merge(xs):
   """ merges the list of dicts (that dont contain includes) and returns a new dict
   where the values of the first dict are updated recursively by the values of the second dict.
   xs -- a list of dicts
   """

Scripts

• pyaconf_render -- loads and merges multiple configs and renders the result in json or yaml format

License

OSI Approved 3 clause BSD License

Prerequisites

• Python 3.7+

Installation

If prerequisites are met, you can install pyaconf like any other Python package, using pip to download it from PyPI:

$ pip install pyaconf

or using setup.py if you have downloaded the source package locally:

$ python setup.py build
$ sudo python setup.py install