Enhanced YAML loading and dumping.
Project description
yamling
Yamling is a YAML handling library that provides enhanced loading and dumping capabilities for YAML files. It builds upon PyYAML to offer additional features like environment variable support, file inclusion, and Jinja2 template resolution.
Special mentions also to pyyaml_env_tag
as well as pyyaml-include
, this library exposes these YAML extensions with a unified interface.
Loading YAML
Basic Loading
To load YAML content from a string:
from yamling import load_yaml
# Simple YAML loading
data = load_yaml("""
name: John
age: 30
""")
To load from a file:
from yamling import load_yaml_file
# Load from local file
config = load_yaml_file("config.yaml")
# Load from remote file (S3, HTTP, etc.)
remote_config = load_yaml_file("s3://bucket/config.yaml")
Safety Modes
Yamling supports three safety modes when loading YAML:
# Safe mode - most restrictive, recommended for untrusted input
data = load_yaml(content, mode="safe")
# Full mode - allows some additional types but restricts dangerous ones
data = load_yaml(content, mode="full")
# Unsafe mode - allows all YAML features (default)
data = load_yaml(content, mode="unsafe")
Warning Always use "safe" mode when loading untrusted YAML content to prevent code execution vulnerabilities.
File Inclusion
Yamling supports including other YAML files using the !include
tag:
# main.yaml
database:
!include db_config.yaml
logging:
!include logging_config.yaml
When loading, specify the base path for includes:
config = load_yaml_file("main.yaml", include_base_path="configs/")
Environment Variables
Use the !ENV
tag to reference environment variables:
database:
password: !ENV DB_PASSWORD
host: !ENV ${DB_HOST:localhost} # with default value
Template Resolution
Yamling can resolve Jinja2 templates in YAML:
from jinja2 import Environment
import yamling
env = Environment()
yaml_content = """
message: "Hello {{ name }}!"
"""
data = load_yaml(
yaml_content,
resolve_strings=True,
jinja_env=env
)
Inheritance
YAML files can inherit from other files using the INHERIT
key:
# base.yaml
database:
host: localhost
port: 5432
# prod.yaml
INHERIT: base.yaml
database:
host: prod.example.com
Load with inheritance enabled:
config = load_yaml_file("prod.yaml", resolve_inherit=True)
Dumping YAML
To serialize Python objects to YAML:
from yamling import dump_yaml
data = {
"name": "John",
"scores": [1, 2, 3],
"active": True
}
yaml_string = dump_yaml(data)
Dataclasses and Pydantic v2 models can also get dumped.
Custom Class Mapping
Map custom classes to built-in types for YAML representation:
from collections import OrderedDict
data = OrderedDict([("b", 2), ("a", 1)])
yaml_string = dump_yaml(data, class_mappings={OrderedDict: dict})
Custom Loader Configuration
For advanced use cases, you can create a custom loader:
from yamling import get_loader
import yaml
# Create custom loader with specific features
loader_cls = get_loader(
yaml.SafeLoader,
include_base_path="configs/",
enable_include=True,
enable_env=True,
resolve_strings=True,
jinja_env=jinja_env,
type_converters={int: str}
)
# Use custom loader
data = yaml.load(content, Loader=loader_cls)
Universal load / dump interface
Yamling provides a universal load function that can handle YAML, JSON, TOML, and INI files. Apart from yaml, only stdlib modules are used, so no additional dependencies are required. Here's a simple example:
import yamling
# Load files based on their extension
config = yamling.load_file("config.yaml") # YAML
settings = yamling.load_file("settings.json") # JSON
params = yamling.load_file("params.toml") # TOML
# Or explicitly specify the format
data = yamling.load_file("config.txt", mode="yaml")
# Load directly from strings
yaml_text = """
name: John
age: 30
"""
data = yamling.load(yaml_text, mode="yaml")
# same in other direction
json_text = yamling.dump(data, mode="json")
yaml.dump_file("config.yaml", data)
Note If orjson is installed, the loader will automatically use it for JSON parsing / dumping, offering significantly better performance compared to the standard
json
module.
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