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IEX-DOWNLOAD: Rust-Powered Access to IEX Historical Data

Project Goal IEX-DOWNLOAD is a robust command-line utility, written in pure Rust, for retrieving IEX TOPS, DEEP, and DEEP+ historical datasets. It provides fast, reliable downloads from the official IEX historical feed, making it trivial to bootstrap your research pipeline with over 13 TB of market data (4,600+ files) spanning 2016–2025.

It succeeds the original Node.js IEX Download project, preserving its automation features while adding the performance, safety, and reliability of Rust.

The Problem Obtaining historical tick-level data from exchanges is often messy and error-prone:

  • Manual: the official interface forces tedious, one-by-one downloads.
  • Unreliable: network hiccups and partial transfers force restarts.
  • Unstructured: managing thousands of files across years of trading days is cumbersome.

The Solution IEX-DOWNLOAD brings together the automation of the original Node.js version with the performance of Rust:

  • Performs: Rust delivers speed, safety, and reliability at scale.
  • Flexible date ranges: download a single day or entire multi-year spans in one command.
  • Dataset choice: selectively fetch TOPS, DEEP, or DEEP+ feeds.
  • Dry-run mode: preview download size and files before committing.
  • Reliable transfers: built-in retries, resumable downloads, and graceful handling of stalled connections.
  • Organized output: automatically stores datasets by feed and date, consistent with IEX conventions.
  • Simple CLI: no fragile scripts, just a single command.
  • Complete coverage: supports all available feeds since December 2016.

Why It Matters Market researchers, quants, and engineers need raw truth data to test ideas and power analytics. With IEX-DOWNLOAD, you don’t just get a handful of samples—you unlock the entire IEX historical feed, 13+ terabytes strong, reliably and reproducibly, without wrestling with brittle tooling.

Paired with IEX2H5, the Rust downloader + C++ converter form a complete pipeline: download terabytes of PCAPs → convert into compressed HDF5 arrays → analyze at scale.

Explore the Project GitHub: github.com/vargaconsulting/iex-download Docs: vargaconsulting.github.io/iex-download