Parquet Conversion Toolkit

8 practical Python utilities for working with CSV, Excel, JSON, JSONL and Parquet files.

This toolkit provides simple, standalone command-line tools for converting data between common formats, with Parquet as the central format.

All tools process files locally on your machine. No web server, API keys or external conversion service is required.

Included Utilities

• CSV to Parquet - Convert CSV files to Parquet with schema inference and streaming processing.
• Parquet to CSV - Convert Parquet files to CSV using batch processing.
• Excel to Parquet - Convert Excel worksheets to Parquet with streaming row processing.
• Parquet to Excel - Export Parquet data to Excel with support for large datasets and worksheet splitting.
• JSON to Parquet - Convert JSON arrays and JSONL data to Parquet, including nested structures.
• Parquet to JSON - Convert Parquet files to standard JSON while preserving nested structures.
• JSONL to Parquet - Convert newline-delimited JSON files to Parquet using streaming processing.
• Generate Test CSV - Generate configurable test datasets with realistic sample data, custom columns and row counts.

Conversion Paths

• CSV → Parquet
• Excel → Parquet
• JSON → Parquet
• JSONL → Parquet
• Parquet → CSV
• Parquet → Excel
• Parquet → JSON

Privacy & Local Processing

Your files are processed directly on your machine and are not uploaded to a website or third-party conversion service.

This makes the toolkit useful for internal datasets, customer data, financial data, confidential reports and other files that should remain local.

Package Contents

• 8 complete Python utilities
• Full source code
• Automated tests
• Example input files
• Individual README documentation
• Individual requirements.txt files

Each utility is independent and can be used, understood, customized and integrated into your own workflows.

Requirements

• Python 3.11 or newer
• Windows, macOS or Linux
• pip

Getting Started

1. Choose a utility from the scripts directory.
2. Install its requirements:

pip install -r requirements.txt

3. Run the utility. For example:

python csv_to_parquet.py input.csv output.parquet

Every utility includes its own README with command-line options and usage examples.