pyflexcfg 0.3.0

Flexible configuration handler for Python projects.

PyFlexCfg

Flexible configuration handler for Python projects.

Description

PyFlexCfg allows you to store your project's configuration in YAML files and seamlessly load them as a unified object when imported into your Python code.

Features:

• YAML-based config: Organize your project's settings using easy-to-read YAML files within nested directories to logically group your configurations.
• Unified Access: Load all configuration files as a single object for easy access.
• Values Override: Dynamically override configuration values using environment variables.
• Secrets Management: Encrypt and decrypt sensitive data directly within your configuration files.

Installation

pip install pyflexcfg

Configuration

There are several environment variables that could be set in order to adjust PyFlexCfg behaviour:

1. By default, PyFlexCfg looks for configuration files in a directory config within the current working directory. To specify a different path, define an environment variable with the absolute path to the desired configuration root directory:

   PYFLEX_CFG_ROOT_PATH=\path\to\config
   

2. In order to use encrypted configuration values, you must set an environment variable with encryption key, which will be used for secrets decryption:

   PYFLEX_CFG_KEY=super_secret_key
   

Basic Usage

Assuming the following configuration file structure:

    \project  <-- working directory
        ├─ config
            ├─ general.yaml
            ├─ env
                ├─ dev.yaml
                ├─ prd.yaml

And each YAML file contains a configuration option like this:

data: test

You can load and use the configurations as follows:

from pyflexcfg import Cfg

print(Cfg.general.data)  # Access data from general.yaml
print(Cfg.env.dev.data)  # Access data from env/dev.yaml
print(Cfg.env.prd.data)  # Access data from env/prd.yaml

Note: Directory and file names in your configuration structure must be compatible with Python attribute naming conventions.

Overriding values with Environment Variables

You can override values in YAML files using environment variables. To do this, create environment variables that reflect the configuration values you want to override. This feature is particularly useful in environments like Docker Compose, where you can pass environment-specific settings to containers dynamically, enabling seamless configuration management across different deployment setups.

For example, if you want to overwrite the value of

Cfg.env.dev.data

Define an environment variable:

CFG__ENV__DEV__DATA=some_value

Having that set, call the method

from pyflexcfg import Cfg

Cfg.update_from_env()

The value from the environment variable will replace the corresponding value from the YAML file.

Handling secrets

Any sensitive data present in configuration files should be encrypted!

Encrypting a Secret

Use the AESCipher class to encrypt your secrets:

from pyflexcfg import AESCipher

aes = AESCipher('secret-key')
aes.encrypt('some-secret-to-encrypt')

This will produce an output like:

b'A1u6BIE2xGtYTSoFRE83H0VHsAW3nrv4WB+T/FEAj1fsh8HIId9r/Rskl0bnDHTI'

Store the encrypted secret in a YAML file with the !encr prefix:

my_secret: !encr b'A1u6BIE2xGtYTSoFRE83H0VHsAW3nrv4WB+T/FEAj1fsh8HIId9r/Rskl0bnDHTI'

Decrypting Secrets

When PyFlexCfg loads the configuration and the environment variable PYFLEX_CFG_KEY is set with your encryption key, it will automatically decrypt values marked with !encr prefix and store them in Cfg as a Secret strings, masking them in logs and console outputs with ******.

Use the AESCipher class to manually decrypt your secrets if needed:

from pyflexcfg import AESCipher

aes = AESCipher('secret-key')
aes.decrypt(b'A1u6BIE2xGtYTSoFRE83H0VHsAW3nrv4WB+T/FEAj1fsh8HIId9r/Rskl0bnDHTI')