Welcome to PardoX

PyPI version License: MIT Powered By Rust Version

The Speed of Rust. The Simplicity of Python.

PardoX is a high-performance DataFrame engine designed for modern data engineering. It combines the safety and speed of a Rust Core with the ease of use of Python, PHP, and Node.js SDKs — allowing you to process massive datasets and integrate with any database without learning a new language.


🚀 Why PardoX?

  • Zero-Copy Architecture: Data flows directly from disk or database into memory-mapped Rust buffers — no Python objects, no intermediate copies.
  • SIMD Acceleration: Mathematical operations use AVX2/NEON CPU instructions for 5x–20x speedups vs. Python loops.
  • Universal Compatibility: Runs natively on Windows, Linux, and macOS (Intel & Apple Silicon).
  • Native Database Engine: Connect to PostgreSQL, MySQL, SQL Server, and MongoDB entirely through Rust — no Python database drivers required.
  • Multi-SDK: A single Rust core powers identical APIs in Python, Node.js, and PHP.
  • Native Format: The .prdx binary format enables ~4.6 GB/s read throughput for repeated workloads.

📚 Documentation

🏁 Getting Started

  • Installation — Setup guide for Python, Node.js, and PHP.
  • Quick Start — Build your first ETL pipeline in 5 minutes.
  • Roadmap — What’s coming in v0.4 and beyond.

📘 User Guide

  • Input / Output — Multi-threaded CSV, native .prdx format, Apache Arrow bridge.
  • Databases — PostgreSQL, MySQL, SQL Server, MongoDB — read, write, and execute.
  • Data Mutation — Vectorized arithmetic, type casting, sorting, data cleaning.
  • Aggregations & Observer — Metrics, statistics, value counts, and full-DataFrame export.
  • GPU Acceleration — GPU Bitonic sort and CPU fallback.
  • ML Integration — Zero-copy NumPy bridge and Scikit-Learn compatibility.

⚙️ API Reference

  • Full Reference — Detailed documentation of all classes, functions, and methods.
  • FFI Exports Reference — All 181 C-ABI functions exported by the Rust core across 5 crates. Use this to build custom bindings or validate SDK integrations.

📂 Base Knowledge

📘 SDK Documentation

📓 Examples & Notebooks


📦 Quick Install

pip install pardox

What’s New in v0.3.4

Pillar What was added
SQL Cursor API (Gap 30) query_to_results(conn, query, batch_size) — streaming iterator over PostgreSQL results yielding DataFrame batches with O(batch) RAM. sql_to_parquet(conn, query, pattern, chunk_size) — stream SQL → PardoX binary files using {i} pattern. Validated: 3 SDKs × 11/11 tests. Requested by GitHub @Prussian1870
30 Gaps Total Gap 30 (SQL Cursor API) added to all 3 SDKs — Python, JavaScript, PHP

What’s New in v0.3.3

Pillar What was added
SQL Cursor API — Rust Core SqlCursor struct with server-side PostgreSQL DECLARE ... NO SCROLL CURSOR. 5 new FFI exports: pardox_scan_sql_cursor_open, pardox_scan_sql_cursor_fetch, pardox_scan_sql_cursor_offset, pardox_scan_sql_cursor_close, pardox_scan_sql_to_parquet. Zero warnings, zero errors

What’s New in v0.3.2

Pillar What was added
PRDX Streaming to PostgreSQL write_sql_prdx() — stream any .prdx file directly to PostgreSQL via COPY FROM STDIN with O(block) RAM. Validated: 150M rows / 3.8 GB in ~490s at ~300k rows/s (Python/JS)
Gaps 1–5 — All SDKs GroupBy, String & Date ops, Decimal type, Window functions, Lazy pipeline — validated across Python, JavaScript, and PHP SDKs
Gaps 7–14 — Python GPU compute, Pivot & Melt, Time Series Fill, Nested Data (JSON), Spill to Disk, Universal Loader (PRDX), SQL over DataFrames
Gaps 15–29 — Python Cloud Storage, Live Query, WebAssembly, Encryption, Data Contracts, Time Travel, Arrow Flight, Distributed Cluster, Linear Algebra, REST Connector
VAP31 & VAP32 CSV→PostgreSQL and PRDX→PostgreSQL integrations validated in 3 SDKs
29 Gaps Total All 29 feature gaps from the original roadmap implemented in the Rust core
FFI Reference Complete documentation of all 181 C-ABI exports across 5 crates

What’s New in v0.3.1

Pillar What was added
Relational Conqueror Native read/write/execute for PostgreSQL, MySQL, SQL Server, MongoDB via Rust drivers
The Observer to_dict(), to_json(), value_counts(), unique() — full-DataFrame export with proper heap memory management
Native Math df.add(), df.sub(), df.std(), df.min_max_scale(), df.sort_values() — pure Rust arithmetic
GPU Awakening sort_values(gpu=True) — WebGPU Bitonic sort with automatic CPU fallback
ML Integration Zero-copy NumPy bridge via __array__ protocol — direct pointer into Rust buffer
PHP & Node.js SDKs Full parity with Python SDK across all new features

Open Source Project distributed under the MIT License.

More info: www.pardox.io


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