Human-friendly YAML formatting with intelligent sequence handling and priority key ordering
Project description
YAML for Humans
Human-friendly YAML formatting for PyYAML that makes YAML more readable and intuitive.
Features
- Empty line preservation: Maintains empty lines from original YAML for better readability
- Intelligent sequence formatting: Strings on same line as dash (
- value), objects on separate lines - Indented sequences: Dashes are properly indented under their parent containers
- Priority key ordering: Important keys like
name,image,commandappear first in mappings - Multi-document support: Handle multiple YAML documents with proper
---separators - Kubernetes manifest ordering: Automatic resource ordering following best practices
- Valid YAML output: All generated YAML passes standard YAML validation
- Drop-in replacement: Compatible with existing PyYAML code
Quick Start
from yaml_for_humans import dumps, dump, load_with_formatting
# Your data
data = {
'containers': [
{
'ports': [8080, 9090],
'name': 'web-server', # name will appear first
'image': 'nginx:latest',
'command': ['/bin/sh', '-c', 'nginx -g "daemon off;"']
}
]
}
# Generate human-friendly YAML
yaml_output = dumps(data)
print(yaml_output)
# Or load existing YAML with formatting preservation
formatted_data = load_with_formatting('existing-config.yaml')
preserved_output = dumps(formatted_data, preserve_empty_lines=True)
Output:
containers:
-
name: web-server # Priority keys first
image: nginx:latest
command:
- /bin/sh # Strings inline with dash
- -c
- nginx -g "daemon off;"
ports:
- 8080
- 9090
Comparison with Standard PyYAML
Standard PyYAML Output
containers:
- command:
- /bin/sh
- -c
- nginx -g "daemon off;"
image: nginx:latest
name: web-server
ports:
- 8080
- 9090
YAML for Humans Output
containers:
-
name: web-server
image: nginx:latest
command:
- /bin/sh
- -c
- nginx -g "daemon off;"
ports:
- 8080
- 9090
Key Differences
- Indented sequences: Dashes are indented under parent containers for better hierarchy visualization
- Priority key ordering: Important keys (
apiVersion,kind,metadata,name,image,imagePullPolicy,env,envFrom,command,args) appear first - Smart formatting: Complex objects use separate lines, simple strings stay inline
- Consistent indentation: Maintains visual hierarchy throughout the document
Whitespace Preservation
YAML for Humans can preserve empty lines and whitespace from the original YAML to maintain document structure and readability:
from yaml_for_humans import load_with_formatting, dumps
# Load a real Kustomization file with strategic empty lines
data = load_with_formatting('tests/test-data/kustomization-compressed.yaml')
# Preserve original whitespace structure
preserved_output = dumps(data, preserve_empty_lines=True)
print("With whitespace preservation:")
print(preserved_output)
# Standard compact output
compact_output = dumps(data, preserve_empty_lines=False)
print("\nCompact output:")
print(compact_output)
With whitespace preservation:
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
resources:
- ../../.overlays/gitlab-registry-access/
- ../../.overlays/postgres-headless-2023/
- django/
labels:
-
includeSelectors: true
pairs:
env: prod
images:
-
name: application
newName: v3.3.2
-
name: nginx
newTag: 1.27.4
configMapGenerator:
-
behavior: create
envs:
- vars.env
name: env
-
files:
- nginx.conf
name: proxy-config
secretGenerator:
-
behavior: create
envs:
- secrets.env
name: env
patches:
-
path: patches/sidecars/nginx-front.yaml
target:
kind: Deployment
labelSelector: component=django
-
path: patches/init-containers/migrate.yaml
target:
kind: Deployment
labelSelector: component=django
-
path: patches/init-containers/collectstatic.yaml
target:
kind: Deployment
labelSelector: component=django
Compact output:
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
resources:
- ../../.overlays/gitlab-registry-access/
- ../../.overlays/postgres-headless-2023/
- django/
labels:
-
includeSelectors: true
pairs:
env: prod
images:
-
name: application
newName: v3.3.2
-
name: nginx
newTag: 1.27.4
configMapGenerator:
-
behavior: create
envs:
- vars.env
name: env
-
files:
- nginx.conf
name: proxy-config
secretGenerator:
-
behavior: create
envs:
- secrets.env
name: env
patches:
-
path: patches/sidecars/nginx-front.yaml
target:
kind: Deployment
labelSelector: component=django
-
path: patches/init-containers/migrate.yaml
target:
kind: Deployment
labelSelector: component=django
-
path: patches/init-containers/collectstatic.yaml
target:
kind: Deployment
labelSelector: component=django
This feature is especially useful for:
- Kustomization files where empty lines separate different resource types and configurations
- Kubernetes manifests where empty lines logically group related settings
- CI/CD pipelines where empty lines help distinguish workflow stages
- Configuration files where whitespace enhances visual structure and readability
CLI Empty Line Preservation
The command-line tool preserves empty lines by default:
# Default behavior (no empty line preservation)
cat kustomization.yaml | huml
# Preserve empty lines
cat kustomization.yaml | huml -P
Installation
Install the core library:
uv add yaml-for-humans
Or install with CLI support:
uv add yaml-for-humans[cli]
Development Installation
For development, install in editable mode:
# Install the package in editable mode
uv pip install -e .
# Or with CLI dependencies for development
uv pip install -e .[cli]
Then import and use:
from yaml_for_humans import dumps, dump, load_with_formatting
Command Line Interface (Optional)
The huml command-line utility converts YAML or JSON input to human-friendly YAML. It accepts input through stdin pipes or file processing:
# Convert JSON to human-friendly YAML
echo '{"name": "web", "ports": [80, 443]}' | huml
# Process existing YAML files
cat config.yaml | huml
# Use with kubectl
kubectl get deployment -o yaml | huml
# Process multi-document YAML (auto-detected)
cat manifests.yaml | huml
# Process JSON input (automatic detection)
echo '{"containers": [...]}' | huml
# Custom indentation
cat config.yaml | huml --indent 4
# Custom stdin timeout (default: 2000ms)
cat config.yaml | huml --timeout 100
# Use unsafe YAML loader (allows arbitrary Python objects - use with caution)
cat config-with-python-objects.yaml | huml --unsafe-inputs
# Process JSON Lines format (one JSON object per line)
cat logs.jsonl | huml
# Handle Kubernetes API responses with items arrays
kubectl get deployments -o json | huml # Automatically splits items into documents
# Process file inputs instead of stdin
huml --inputs config.yaml,deploy.json
# Process multiple files with glob patterns
huml --inputs "*.json,configs/*.yaml"
# Process all files in a directory (add trailing slash)
huml --inputs /path/to/configs/
# Mix glob patterns, directories, and explicit files
huml --inputs "*.json,/configs/,specific.yaml"
# Output to file or directory
kubectl get all -o json | huml --output ./k8s-resources/
Stdin Input Handling
The CLI automatically detects input format and handles:
- JSON objects: Single objects or arrays
- JSON Lines: Multiple JSON objects, one per line
- YAML documents: Single or multi-document with
---separators - Kubernetes API responses: Objects with
itemsarrays are split into separate documents - Format detection: Automatic detection based on content analysis
CLI Options
-i, --inputs TEXT: Comma-delimited list of JSON/YAML file paths to process. Supports:- Explicit file paths:
config.yaml,deploy.json - Glob patterns:
*.json,configs/*.yaml - Directories:
/path/to/directory/(must end with/) - Mixed combinations:
*.json,/configs/,specific.yaml
- Explicit file paths:
-o, --output TEXT: Output file or directory path (if ends with/, treated as directory)--auto: Automatically create output directories if they don't exist--indent INTEGER: Indentation level (default: 2)-t, --timeout INTEGER: Stdin timeout in milliseconds (default: 2000)-u, --unsafe-inputs: Use unsafe YAML loader (allows arbitrary Python objects, use with caution)-P, --preserve-empty-lines: Preserve empty lines from original YAML (default: false)--help: Show help message--version: Show version information
Input Processing Behavior
- File Globbing: Patterns like
*.jsonandconfigs/*.yamlare expanded to match files - Directory Processing: Paths ending with
/process all valid JSON/YAML files in the directory - Invalid File Handling: Files that can't be parsed or aren't JSON/YAML are skipped with warnings
- Robust Processing: Processing continues even if some files fail, reporting errors but not stopping
- Format Detection: Files are validated based on extension (
.json,.yaml,.yml,.jsonl) and content analysis
Multi-Document Support
Basic Multi-Document Usage
from yaml_for_humans import dumps_all, dump_all
documents = [
{'config': {'version': '1.0', 'features': ['auth', 'logging']}},
{'services': [{'name': 'web', 'image': 'nginx'}]},
{'metadata': {'created': '2025-01-01'}}
]
# Generate multi-document YAML
yaml_output = dumps_all(documents)
print(yaml_output)
Output:
config:
version: '1.0'
features:
- auth
- logging
---
services:
-
name: web
image: nginx
---
metadata:
created: '2025-01-01'
Kubernetes Manifests
from yaml_for_humans import dumps_kubernetes_manifests
manifests = [
{'apiVersion': 'apps/v1', 'kind': 'Deployment', ...},
{'apiVersion': 'v1', 'kind': 'Service', ...},
{'apiVersion': 'v1', 'kind': 'ConfigMap', ...},
{'apiVersion': 'v1', 'kind': 'Namespace', ...}
]
# Automatically orders resources: Namespace, ConfigMap, Service, Deployment
ordered_yaml = dumps_kubernetes_manifests(manifests)
API Reference
For detailed API documentation, see API.md.
Testing
Run the test suite with pytest:
uv run pytest tests/ -v
Test Coverage
- Unit tests: Core emitter functionality, key ordering, YAML validity
- Integration tests: Real-world examples including Kubernetes manifests, Docker Compose files, CI/CD pipelines
- Round-trip tests: Ensure generated YAML can be parsed back correctly
Examples
Run the example scripts to see the formatting in action:
uv run python examples/kubernetes_example.py
uv run python examples/docker_compose_example.py
uv run python examples/multi_document_example.py
uv run python examples/kubernetes_manifests_example.py
The examples demonstrate:
- Kubernetes deployments with priority key ordering
- Docker Compose files with intelligent sequence formatting
- Multi-document YAML with proper separators
- Kubernetes manifest ordering and resource prioritization
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