🧩 Python Automation Recipes – ⚙️ Config Validator

Posted on: June 22, 2026

Description:

📌 Introduction

Automation workflows often depend on configuration files. But if a config is missing required fields or has invalid values, the automation may fail halfway through execution.

This recipe shows how to validate JSON/YAML configs before execution, so your scripts can catch issues early and fail safely.

🔎 Explanation

The script loads a config file.
It checks whether all required fields exist.
It validates basic value types like strings, lists, and booleans.
If validation fails, it prints clear errors.
If validation passes, the automation can safely continue.

This is useful before running workflow runners, scheduled jobs, backup scripts, or deployment automations.

✅ Key Takeaways

⚙️ Validate configs before running automation tasks.
🚨 Catch missing or invalid fields early.
🧩 Makes automation workflows safer and more reliable.

📄 Sample `config.json`

{
  "workflow_name": "daily_automation",
  "enabled": true,
  "tasks": [
    "backup_folder",
    "clean_logs",
    "send_report"
  ]
}

Code Snippet:

import json
from pathlib import Path

# --- Step 1: Configure config file path ---
CONFIG_FILE = Path("config.json")

# --- Step 2: Define required config schema ---
REQUIRED_FIELDS = {
    "workflow_name": str,
    "enabled": bool,
    "tasks": list,
}

# --- Step 3: Load JSON config ---
def load_config(file_path):
    """
    Load and return JSON config data.
    """
    if not file_path.exists():
        raise FileNotFoundError(f"Config file not found: {file_path}")

    with file_path.open("r", encoding="utf-8") as file:
        return json.load(file)

# --- Step 4: Validate config structure ---
def validate_config(config):
    """
    Validate required fields and expected data types.
    """
    errors = []

    for field, expected_type in REQUIRED_FIELDS.items():

        # Check if field exists
        if field not in config:
            errors.append(f"Missing required field: {field}")
            continue

        # Check if field has correct type
        if not isinstance(config[field], expected_type):
            errors.append(
                f"Invalid type for '{field}'. "
                f"Expected {expected_type.__name__}, got {type(config[field]).__name__}"
            )

    # Check that tasks list is not empty
    if "tasks" in config and isinstance(config["tasks"], list):
        if not config["tasks"]:
            errors.append("Tasks list cannot be empty.")

        # Check every task is a string
        for task in config["tasks"]:
            if not isinstance(task, str):
                errors.append("Every task inside 'tasks' must be a string.")

    return errors

# --- Step 5: Run validation ---
try:
    config_data = load_config(CONFIG_FILE)
    validation_errors = validate_config(config_data)

    if validation_errors:
        print("Config validation failed:\n")

        for error in validation_errors:
            print(f"- {error}")

    else:
        print("Config validation passed.")
        print(f"Workflow ready: {config_data['workflow_name']}")

except json.JSONDecodeError as e:
    print("Invalid JSON format.")
    print(f"Error: {e}")

except Exception as e:
    print("Validation failed.")
    print(f"Error: {e}")

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🧩 Python Automation Recipes – ⚙️ Config Validator

Description:

📌 Introduction

🔎 Explanation

✅ Key Takeaways

📄 Sample `config.json`

Code Snippet:

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