PyYAML

Language: Python

CLI/Utils

PyYAML was created by Kirill Simonov in 2006 to provide a simple, Pythonic way to work with YAML. YAML is a human-readable data serialization format commonly used for configuration files, data exchange, and application settings. PyYAML quickly became the standard library for YAML processing in Python.

PyYAML is a Python library for parsing and writing YAML (YAML Ain’t Markup Language) files. It allows you to read YAML data into Python objects and serialize Python objects back into YAML format.

Installation

pip: pip install pyyaml

conda: conda install -c conda-forge pyyaml

Usage

PyYAML provides functions `yaml.load()` and `yaml.safe_load()` to parse YAML into Python objects, and `yaml.dump()` to serialize Python objects into YAML. `safe_load()` is recommended for untrusted input to avoid executing arbitrary Python objects.

Loading YAML from a string

import yaml
yaml_str = 'name: Alice\nage: 30\ncity: New York'
data = yaml.safe_load(yaml_str)
print(data)

Parses a YAML string into a Python dictionary safely.

Loading YAML from a file

import yaml
with open('config.yaml', 'r') as file:
    data = yaml.safe_load(file)
print(data)

Reads a YAML file and converts it into a Python object (usually a dictionary).

Dumping Python object to YAML string

import yaml
data = {'name': 'Alice', 'age': 30, 'city': 'New York'}
yaml_str = yaml.dump(data)
print(yaml_str)

Serializes a Python dictionary into a YAML-formatted string.

Writing YAML to a file

import yaml
data = {'name': 'Alice', 'age': 30, 'city': 'New York'}
with open('output.yaml', 'w') as file:
    yaml.dump(data, file)

Writes Python data structures to a YAML file.

Using custom YAML tags

import yaml
class User:
    def __init__(self, name, age):
        self.name = name
        self.age = age

def user_representer(dumper, data):
    return dumper.represent_mapping('!User', {'name': data.name, 'age': data.age})

yaml.add_representer(User, user_representer)
user = User('Alice', 30)
print(yaml.dump(user))

Demonstrates defining custom YAML tags and serializing Python objects with PyYAML.

Loading multiple documents

import yaml
yaml_str = '---\nname: Alice\n---\nname: Bob'
docs = list(yaml.safe_load_all(yaml_str))
print(docs)

Loads multiple YAML documents from a single string or file using `safe_load_all()`.

Error Handling

yaml.YAMLError: Raised for any parsing or syntax errors. Check your YAML format for indentation and correct syntax.

ConstructorError: Occurs when a custom tag cannot be constructed. Define custom constructors or avoid unsafe tags.

ScannerError: Indicates malformed YAML. Ensure correct indentation, colons, and spacing.

Best Practices

Use `safe_load()` instead of `load()` when processing untrusted YAML input.

Serialize Python objects explicitly using `dump()` with custom representers if needed.

Keep YAML files human-readable and simple for maintainability.

Validate parsed YAML data before using it in your application.

Use `load_all()` to handle multi-document YAML files safely.

Official Docs Github