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How to Convert Between YAML and JSON (Complete Python/JavaScript Guide)

TECHNOLOGY

Why Convert Between YAML and JSON?

In microservice architectures and DevOps practices, we often encounter scenarios like:

  • Configuration management (YAML is more human-readable)
  • API data interchange (JSON is the web standard format)
  • Multi-cloud deployment (different platforms have different format requirements)
  • Data persistence (JSON is easier to compress and store)

Efficient YAML to JSON Conversion with Python

1.1 Preparation

# conda environment
pip install pyyaml

Complete YAML to JSON Conversion Process

import yaml
import json
import sys
import os

def yaml_to_json(yaml_str):
    try:
        data = yaml.safe_load(yaml_str)
        return json.dumps(data, indent=2, ensure_ascii=False, default=str)
    except yaml.YAMLError as e:
        print(f"YAML parsing error: {e.problem} {e.context}")
    except Exception as e:
        print(f"Unknown error: {str(e)}")

if __name__ == "__main__":
    if len(sys.argv) > 1:
        yaml_file = sys.argv[1]
        if not os.path.isfile(yaml_file):
            print(f"File not found: {yaml_file}")
            sys.exit(1)

        with open(yaml_file, 'r', encoding='utf-8') as f:
            yaml_content = f.read()
        
        json_output = yaml_to_json(yaml_content)
        json_file = os.path.splitext(yaml_file)[0] + ".json"
        
        with open(json_file, 'w', encoding='utf-8') as f:
            f.write(json_output)
        
        print(f"Successfully converted YAML to JSON, output file: {json_file}")
    else:
        # Default test data
        yaml_content = """
param:
  Author: Yanzhi
  Email: yanzhi@bobobk.com
  Sample: RNA
  Number: 12
  Source: Lab

data:
  indexdir: /index/
  filedir: /rawdata
  filenames:
    - MERS_set2_0h_1
    - MERS_set2_0h_2
    - MERS_set2_16h_1
    - MERS_set2_16h_2
    - MERS_set2_48h_1
    - MERS_set2_48h_2
    - SARS_0h_1
    - SARS_0h_2
    - SARS_16h_1
    - SARS_16h_2
    - SARS_48h_1
    - SARS_48h_2
"""
        print(yaml_to_json(yaml_content))

{
  "param": {
    "Author": "Yanzhi",
    "Email": "yanzhi@bobobk.com",
    "Sample": "RNA",
    "Number": 12,
    "Source": "Lab"
  },
  "data": {
    "indexdir": "/index/",
    "filedir": "/rawdata",
    "filenames": [
      "MERS_set2_0h_1",
      "MERS_set2_0h_2",
      "MERS_set2_16h_1",
      "MERS_set2_16h_2",
      "MERS_set2_48h_1",
      "MERS_set2_48h_2",
      "SARS_0h_1",
      "SARS_0h_2",
      "SARS_16h_1",
      "SARS_16h_2",
      "SARS_48h_1",
      "SARS_48h_2"
    ]
  }
}

Key Feature Explanation:

python yaml_to_json.py config.yaml

Advanced JSON to YAML Usage

import json
import yaml
import sys
import os

def json_to_yaml(json_str):
    try:
        data = json.loads(json_str)
        return yaml.dump(data, allow_unicode=True, sort_keys=False)
    except json.JSONDecodeError as e:
        print(f"JSON parsing error: {e.msg} at line {e.lineno} column {e.colno}")
    except Exception as e:
        print(f"Unknown error: {str(e)}")

if __name__ == "__main__":
    if len(sys.argv) > 1:
        json_file = sys.argv[1]
        if not os.path.isfile(json_file):
            print(f"File not found: {json_file}")
            sys.exit(1)

        with open(json_file, 'r', encoding='utf-8') as f:
            json_content = f.read()
        
        yaml_output = json_to_yaml(json_content)
        yaml_file = os.path.splitext(json_file)[0] + ".yaml"

        with open(yaml_file, 'w', encoding='utf-8') as f:
            f.write(yaml_output)
        
        print(f"Successfully converted JSON to YAML, output file: {yaml_file}")
    else:
        # Test JSON data (consistent structure with previous YAML test data)
        json_content = """
{
  "param": {
    "Author": "Yanzhi",
    "Email": "yanzhi@bobobk.com",
    "Sample": "RNA",
    "Number": 12,
    "Source": "Lab"
  },
  "data": {
    "indexdir": "/index/",
    "filedir": "/rawdata",
    "filenames": [
      "MERS_set2_0h_1",
      "MERS_set2_0h_2",
      "MERS_set2_16h_1",
      "MERS_set2_16h_2",
      "MERS_set2_48h_1",
      "MERS_set2_48h_2",
      "SARS_0h_1",
      "SARS_0h_2",
      "SARS_16h_1",
      "SARS_16h_2",
      "SARS_48h_1",
      "SARS_48h_2"
    ]
  }
}
"""
        print(json_to_yaml(json_content))

param:
  Author: Yanzhi
  Email: yanzhi@bobobk.com
  Sample: RNA
  Number: 12
  Source: Lab
data:
  indexdir: /index/
  filedir: /rawdata
  filenames:
  - MERS_set2_0h_1
  - MERS_set2_0h_2
  - MERS_set2_16h_1
  - MERS_set2_16h_2
  - MERS_set2_48h_1
  - MERS_set2_48h_2
  - SARS_0h_1
  - SARS_0h_2
  - SARS_16h_1
  - SARS_16h_2
  - SARS_48h_1
  - SARS_48h_2

JavaScript Browser-Side Solution

Browser-side implementation

JSON to YAML

  <script>
    function convertToYaml() {
      const input = document.getElementById("jsonInput").value;
      const output = document.getElementById("yamlOutput");
      try {
        const obj = JSON.parse(input);
        const yaml = jsyaml.dump(obj, { sortKeys: false });
        output.textContent = yaml;
      } catch (e) {
        output.textContent = "❌ JSON parsing error: " + e.message;
      }
    }
  </script>

YAML to JSON

    function convertToJson() {
      const yamlText = document.getElementById("yamlInput").value;
      const output = document.getElementById("outputArea");
      try {
        const obj = jsyaml.load(yamlText);
        const json = JSON.stringify(obj, null, 2);
        output.textContent = json;
      } catch (e) {
        output.textContent = "❌ YAML parsing error: " + e.message;
      }
    }

Online Version

Generate HTML based on the JavaScript version: Online YAML JSON converter

Core Differences and Best Practices

Format Comparison

Feature YAML JSON
Comments Supports # comments Not supported
Data Types Extended types (date, regex) Basic types
Readability High Medium
File Size Smaller Larger
  • Needs human editing? → Choose YAML
  • Needs strict Schema? → Choose JSON
  • Needs cross-platform transfer? → Choose JSON
  • Needs version control? → Choose YAML (differences are clearer)

Common Problem Solutions

Special character escaping: JSON requires escaping double quotes, while YAML supports a mix of single and double quotes.

Date format handling:

# Python custom converter
class SafeDateYamlLoader(yaml.SafeLoader):
    pass

def timestamp_constructor(loader, node):
    return datetime.fromisoformat(loader.construct_scalar(node))

SafeDateYamlLoader.add_constructor('!datetime', timestamp_constructor)

Large file processing techniques: Read and convert in chunks.

Conclusion

Through this detailed guide, you should now have a solid understanding of:

  • The core methods for format conversion in both languages.
  • The best practices for different scenarios.
  • Strategies for handling common issues.

Practical Application Suggestions:

  • Prioritize YAML for configuration management.
  • Recommend JSON format for API interactions.
  • Pay attention to compatibility for complex data types.

Mastering format conversion skills will significantly boost your development efficiency. It’s recommended to combine this with getting a ChatGPT API key for automated script development and building intelligent data processing workflows.

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