name: data-type-converter
description: Convert between data formats (JSON, CSV, XML, YAML, TOML). Handles nested structures, arrays, and preserves data types where possible.

Data Type Converter

Convert data between JSON, CSV, XML, YAML, and TOML formats. Handles nested structures, arrays, and complex data with intelligent flattening options.

Quick Start

from scripts.data_converter import DataTypeConverter

# JSON to CSV
converter = DataTypeConverter()
converter.convert("data.json", "data.csv")

# YAML to JSON
converter.convert("config.yaml", "config.json")

# With options
converter.convert("data.json", "data.csv", flatten=True)

Features

• 5 Formats: JSON, CSV, XML, YAML, TOML
• Nested Data: Flatten or preserve nested structures
• Arrays: Handle array data intelligently
• Type Preservation: Maintain data types where possible
• Pretty Output: Formatted, human-readable output
• Batch Processing: Convert multiple files

API Reference

Basic Conversion

converter = DataTypeConverter()

# Auto-detect format from extension
converter.convert("input.json", "output.csv")
converter.convert("input.xml", "output.json")
converter.convert("input.yaml", "output.toml")

With Options

# Flatten nested structures for CSV
converter.convert("nested.json", "flat.csv", flatten=True)

# Pretty print output
converter.convert("data.json", "pretty.json", indent=4)

# Specify root element for XML
converter.convert("data.json", "data.xml", root="records")

Programmatic Access

# Load and convert in memory
data = converter.load("data.json")
converter.save(data, "data.yaml")

# String conversion
json_str = '{"name": "John", "age": 30}'
yaml_str = converter.convert_string(json_str, "json", "yaml")

Batch Processing

# Convert all JSON files to CSV
converter.batch_convert(
    input_dir="./json_files",
    output_dir="./csv_files",
    output_format="csv"
)

CLI Usage

# Basic conversion
python data_converter.py --input data.json --output data.csv

# With flattening
python data_converter.py --input nested.json --output flat.csv --flatten

# Batch convert
python data_converter.py --input-dir ./json --output-dir ./csv --format csv

# Pretty print
python data_converter.py --input data.json --output pretty.json --indent 4

CLI Arguments

Conversion Matrix

Examples

JSON to CSV (Flat)

converter = DataTypeConverter()

# Input: data.json
# [{"name": "John", "age": 30}, {"name": "Jane", "age": 25}]

converter.convert("data.json", "data.csv")

# Output: data.csv
# name,age
# John,30
# Jane,25

Nested JSON to Flat CSV

# Input: nested.json
# [{"user": {"name": "John", "email": "[email protected]"}, "orders": 5}]

converter.convert("nested.json", "flat.csv", flatten=True)

# Output: flat.csv
# user.name,user.email,orders
# John,[email protected],5

YAML Config to JSON

# Input: config.yaml
# database:
#   host: localhost
#   port: 5432
# debug: true

converter.convert("config.yaml", "config.json")

# Output: config.json
# {"database": {"host": "localhost", "port": 5432}, "debug": true}

XML to JSON

# Input: data.xml
# <users>
#   <user><name>John</name><age>30</age></user>
# </users>

converter.convert("data.xml", "data.json")

# Output: data.json
# {"users": {"user": {"name": "John", "age": "30"}}}

Dependencies

pyyaml>=6.0
toml>=0.10.0
xmltodict>=0.13.0
pandas>=2.0.0

Limitations

• CSV doesn't support nested data (requires flattening)
• XML attribute handling is basic
• TOML doesn't support null values
• Very deep nesting may cause issues with some formats
• Array handling varies by format