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SciQLop — Space Physics Data, Made Simple

Browse, visualize, and analyze in situ plasma measurements from 70+ space missions — without fighting file formats, server APIs, or slow tools.

SciQLop in action — browsing MMS data

The Problem

Space physicists deal with data scattered across multiple archives (CDAWeb, AMDA, CSA, SSCWeb, ...), each with its own API, file formats, and quirks. Downloading, reading, and cross-comparing multi-mission data involves too much plumbing and not enough science.

Our Solution

An ecosystem of open-source tools that handle the plumbing for you:

pip install speasy — Get Any Data in One Line

Access 65,000+ data products from AMDA, CDAWeb, CSA, SSCWeb, and CDPP 3DView through a single Python API. No file downloads, no format headaches.

import speasy as spz

# Grab IMF data — that's it
imf = spz.get_data("amda/imf", "2016-06-02", "2016-06-05")

# Works with NumPy, Pandas, Matplotlib out of the box
imf.plot()

Transparent caching (local + shared proxy), automatic inventory discovery, tab-completion in notebooks. Also available in Julia.

Download SciQLop — Interactive GUI for Data Exploration

A desktop application for fluid, lag-free browsing of multivariate time series — even on gigabyte-scale datasets.

  • Drag & drop products from any supported archive
  • Scroll & zoom seamlessly — data downloads transparently at plot edges
  • Virtual products — write a Python function, see it recomputed live as you navigate
  • Event catalogs — label intervals graphically, build catalogs as easily as bookmarking web pages — and co-edit them in real time with colleagues
  • JupyterLab inside — hybrid interactive + programmatic workflows
  • App Store & AI assistant — install community plugins from the built-in App Store, including AI chat backends that can plot and fetch data for you

Available as AppImage (Linux), DMG (macOS), or Windows installer — grab one from the latest release.

Drag and drop data products

pip install pycdfpp — CDF Files, Fast

A modern C++ CDF library with Python bindings. Thread-safe, up to 4 GB/s read speed, no legacy baggage.

import pycdfpp

cdf = pycdfpp.load("my_data.cdf")
bx = cdf["Bx_GSE"]

The Full Stack

Layer Tool What it does
GUI SciQLop Interactive desktop app for browsing & labeling data
Plotting SciQLopPlots High-performance C++ rendering for large datasets
Data access Speasy Unified API for all major space physics archives
CDF I/O CDFpp + PyISTP Fast, thread-safe CDF reading/writing + ISTP metadata
Catalogs tscat / cocat Event catalogs with real-time CRDT-based collaborative editing
Infrastructure speasy_proxy Shared caching proxy — less load on public archives
Julia Speasy.jl Julia bindings for Speasy

Get Started

SciQLop GUI — download a ready-to-run build for your platform from the latest release: AppImage (Linux), DMG (macOS), or Windows installer.

Speasy (the data-access library) installs from PyPI:

pip install speasy

Links