Skip to main content

Modular Yaml for configuration management

Project description

ModYaml

ModYaml is a Python module designed for advanced YAML configuration management, offering modular, flexible, and powerful configuration capabilities.

Purpose

The primary purpose of ModYaml is to enhance YAML configurations by providing:

  1. Modular configuration through file inclusion
  2. Support for various file sources (local, remote, cloud storage)
  3. Environment variable interpolation
  4. Jinja2 templating support

These features allow for more dynamic, reusable, and environment-aware configurations.

Syntax

ModYaml extends standard YAML syntax with the !include directive:

key: !include path/to/another/file.yaml

The path/to/another/file.yaml can be: A local file path A URL (http, https, ftp, etc.) A cloud storage path (s3://, gs://, etc.)

ModYaml uses fsspec (Filesystem Specification) to handle file access, supporting a wide range of file systems and protocols.

database:
  !include configs/database.yaml
logging:
  !include https://example.com/logging-config.yaml
cloud_settings:
  !include gs://my-bucket/cloud-config.yaml

Processing Stages

ModYaml processes your configuration in the following stages:

  1. File Loading: The main YAML file is loaded, and all !include directives are resolved recursively.
  2. YAML Parsing: The complete YAML structure (including included files) is parsed into a Python dictionary.
  3. Jinja2 Templating: The parsed YAML is rendered as a Jinja2 template, allowing for dynamic content generation.
  4. Environment Variable Interpolation: Environment variables are interpolated into the configuration.
  5. Final Parsing: The resulting string is parsed again as YAML to produce the final configuration dictionary.

Using Environment Variables

Environment variables can be used in your YAML files for flexible configuration and debugging. They are accessible in the Jinja2 templating stage.

Example:

debug_mode: {{ DEBUG | default('false') }}
database_url: {{ DB_URL | default('localhost:5432') }}

Debugging configs

It is possible to trigger the config flow processing debug to standard logger. In order to do this, the following environment variables can be used:

export MODYAML_LOG_LEVEL=DEBUG

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

modyaml-0.0.post15.tar.gz (3.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

modyaml-0.0.post15-py3-none-any.whl (2.8 kB view details)

Uploaded Python 3

File details

Details for the file modyaml-0.0.post15.tar.gz.

File metadata

  • Download URL: modyaml-0.0.post15.tar.gz
  • Upload date:
  • Size: 3.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for modyaml-0.0.post15.tar.gz
Algorithm Hash digest
SHA256 3930c827639ba196aecd6c8812e5df07827d4a48e46a312ae65a7428198c49d8
MD5 cf4c9dcac9bf9bd7c534024b374c6038
BLAKE2b-256 be41deb793b8642f798f3e65669a2ee8489d12ad4006cb31c411f53075dff5a1

See more details on using hashes here.

File details

Details for the file modyaml-0.0.post15-py3-none-any.whl.

File metadata

  • Download URL: modyaml-0.0.post15-py3-none-any.whl
  • Upload date:
  • Size: 2.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for modyaml-0.0.post15-py3-none-any.whl
Algorithm Hash digest
SHA256 0a3d4873c5ac5cb5a08249065aa750b45ce608ab9cf28971fb87a2679b31324b
MD5 67fbfe633613184adf9c1fa8e0f6572d
BLAKE2b-256 40d5883cc06b78aaa8ba68670aea4ed1295987f09ab2e18e9681f6c6933b20e9

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page