Supprimer Rendre public Rendre privé Add tags Delete tags
  Ajouter un tag   Annuler
  Supprimer le tag   Annuler
  • • DevOps notes •
  •  
  • Tags
  • Connexion

Working with YAML files/shaare/d2D1ag

  • python
  • python

Working with YAML files

  • YAML (“YAML Ain’t Markup Language”) focuses on human readability. Indentation replaces braces and brackets, comments are allowed, and quoting is usually optional.
  • DevOps tooling (Kubernetes, Ansible, GitHub Actions, many app configs) standardizes on YAML for its clarity and brevity.
  • JSON is excellent for machine-to-machine communication, but its strict syntax (no comments, heavy quoting) can feel verbose to humans maintaining config files.
  • Python’s standard library lacks YAML support; PyYAML is the community-standard package to fill that gap.

YAML Syntax and Features

  • Structure comes from spaces for indentation: tabs are discouraged.
  • Mappings use key: value; sequences use a leading hyphen (-) plus a space.
  • Scalars include strings, numbers, booleans (true / false, yes / no), and null.
  • Comments begin with #.
  • Multi-line scalars can be literal (|) or folded (>).
  • *Anchors (&) and aliases ()** avoid repetition by re-using defined blocks.
  • YAML is a superset of JSON: most valid JSON documents are also valid YAML.
import yaml, json

snippet = """
service: &svc
  name: user-api
  port: 8080
  enabled: true
  tags:
    - api
    - user
    - internal
staging:
  <<: *svc
  replicas: 2
production:
  <<: *svc
  replicas: 4
"""

parsed = yaml.safe_load(snippet)
print(parsed)

multiline_demo = """
literal: |
  line 1
  line 2
  line 3
folded: >
  This is a long string that
  could go out of screen, so
  we will break this up into
  multiple lines to improve
  readability.
"""
print("\n")
print(yaml.safe_load(multiline_demo))

Deserializing YAML with yaml.safe_load

  • Prefer yaml.safe_load (or passing Loader=yaml.SafeLoader) to prevent arbitrary-code execution; avoid yaml.load on untrusted data.
  • Accepts a string or an open text file handle and returns native Python structures.
  • Wrap calls in try / except yaml.YAMLError to catch malformed input.
import yaml
from pathlib import Path

compose = Path("compose.yaml")

try:
    with compose.open("r", encoding="utf-8") as file:
        config = yaml.safe_load(file)
        print(f"Compose version: {config["version"]}")

        for svc, options in config["services"].items():
            print(f"{svc.capitalize()} image\t: {options["image"]}")
except yaml.YAMLError as e:
    print("YAML error:")
    print(e)

Example of compose.yaml

version: '3.8'
services:
  web:
    image: myapp:latest
    ports:
      - "8000:80"
  redis:
    image: redis:alpine

Serializing Python Objects with yaml.dump

  • Use yaml.dump(obj, indent=2, default_flow_style=False, sort_keys=False) for readable block-style output.
  • Set stream to an open file handle to write directly; leave it None to return a string.
import yaml
from pathlib import Path

python_cfg = {
    "service": {"name": "listener-service", "port": 6789, "workers": 4, "enabled": False},
    "queues": ["high", "default", "low"],
    "retry_policy": None,
}

output_path = Path("listener_config.yaml")

with output_path.open("w", encoding="utf-8") as file:
    yaml.dump(python_cfg, file, sort_keys=False, default_flow_style=False)

Example of listener_config.yaml

service:
  name: listener-service
  port: 6789
  workers: 4
  enabled: false
queues:
- high
- default
- low
retry_policy: null
3 months ago Permalien
cluster icon
  • Numbers, strings : Numbers (int and float) int: Whole numbers (e.g., 10, 1024). No overflow due to arbitrary precision. float: Numbers with decimals (e.g., 3.14159). Us...
  • Enhancing Functions: Decorators : Enhancing Functions: Decorators A decorator is a callable that takes another function, adds behaviour before and/or after it runs, and returns a new ...
  • Lambda Functions : Lambda Functions Python functions defined with def allow multiple statements, clear naming, and support for docstrings, making them ideal for complex...
  • Parametrized Tests : Parametrized Tests Introduction Often, we need to test the same logic with different inputs and outputs, such as validating various IP address or hos...
  • Mocking : Mocking Fundamentals Introduction When unit testing DevOps scripts that interact with external systems, tests can become slow, unreliable, difficult ...


(110)
Filtrer par liens sans tag
Replier Replier tout Déplier Déplier tout Êtes-vous sûr de vouloir supprimer ce lien ? Êtes-vous sûr de vouloir supprimer ce tag ? Le gestionnaire de marque-pages personnel, minimaliste, et sans base de données par la communauté Shaarli