DKIST‑Processing‑Test 1.42.4rc1: New Features, Installation Guide & Quick Start

By Azon Vault On May 6, 2026

Introduction

Sun‑seeking researchers and data analysts, rejoice! The latest release candidate of DKIST‑Processing‑Test – version 1.42.4rc1 – is now available. This update brings performance boosts, new calibration utilities, and streamlined workflow tools that make working with Daniel K. Inouye Solar Telescope (DKIST) data faster and more reliable.

What’s New in 1.42.4rc1?

1. Faster Parallel Processing

Improved Dask integration reduces processing time by up to 30% on multi‑core machines.
Automatic chunk sizing adapts to available RAM, preventing crashes on large data cubes.

2. New Calibration Modules

Dark‑current correction with adaptive scaling for temperature variations.
Polarimetric demodulation using the latest Mueller matrix models.

3. Enhanced Metadata Handling

Full support for FITS header extensions introduced in DKIST Level 2 data.
Convenient dkist-meta CLI tool to query, edit, and export metadata.

4. Bug Fixes & Compatibility

Resolved memory leaks in the vissualize sub‑package.
Compatibility with Python 3.12 and newer NumPy releases.

How to Install 1.42.4rc1

Installation is straightforward using pip. Follow these steps:

Ensure you have Python 3.10+ and a working virtualenv.
```
python -m venv dkist-env source dkist-env/bin/activate
```

Upgrade pip and install the release candidate:

pip install --upgrade pip pip install dkist-processing-test==1.42.4rc1

Verify the installation:

dkist‑test --version # Expected output: dkist‑processing‑test 1.42.4rc1

Quick Start: Processing Your First DKIST Data Cube

Below is a minimal example that demonstrates the new parallel pipeline.

import dkist from dkist.processing import calibrate, align  # Load a raw Level‑1 FITS file cube = dkist.open_fits('raw_observation.fits')  # Apply the new dark‑current and polarimetric calibrations calibrated = calibrate.dark_current(cube) calibrated = calibrate.polarimetric(calibrated)  # Align frames using Dask‑accelerated routine aligned = align.dask_align(calibrated)  # Save the processed Level‑2 product aligned.save('processed_observation.fits')

The align.dask_align function automatically distributes work across all available cores, giving you that performance boost promised in the release notes.

Best Practices for Using the New Features

Check your RAM: For cubes larger than 8 GB, enable the --max‑memory flag to let the library spill to disk safely.
Validate metadata: Run dkist-meta validate processed_observation.fits to catch missing keywords before downstream analysis.
Version control: Pin the exact version (1.42.4rc1) in your requirements.txt to guarantee reproducibility across collaborators.

Where to Find More Information

The full changelog, detailed API docs, and sample notebooks are hosted on the official GitHub repository:

Conclusion

DKIST‑Processing‑Test 1.42.4rc1 is a solid step forward for solar physicists looking to get the most out of DKIST observations. With faster parallel processing, new calibration tools, and robust metadata support, the release reduces the time from raw data to science‑ready products. Install the release candidate today, follow the quick‑start guide, and start exploring the Sun with unprecedented efficiency.