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

--input

--output

--input-dir

--output-dir

--format

--flatten

--indent

--root

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": "j@test.com"}, "orders": 5}]

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

# Output: flat.csv
# user.name,user.email,orders
# John,j@test.com,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