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dmrpp as a chunk reference format

Thu, 12 Nov 2026 11:00:00 -0600

I keep coming back to DMR++. It is a good old idea: instead of making every client parse an HDF5 granule from scratch, publish the map ahead of time. A sidecar gives you dimensions, variables, chunk positions, offsets, and byte lengths. The client follows the references and only fetches what it needs.

That is a proxy. It is not a copy, and it is not a proof.

The reference notebook parses a small DMR++ document, turns the offsets into a VirtualiZarr chunk manifest, and puts the result next to an Icechunk-style manifest.

A reproducible technical blog with Hugo, Quarto, and Pixi

Thu, 12 Nov 2026 09:00:00 -0600

This site is deliberately boring infrastructure: static files generated in CI, deployed to GitHub Pages, with no application server and no database.

The pieces

Layer	Tool	Responsibility
Site generator	Hugo	Pages, taxonomies, RSS, HTML
Theme	rewired	Layouts and retro terminal visual identity
Notebooks	Quarto	Execute and convert `.qmd`/`.ipynb` to Markdown
Environment	Pixi	Pinned Python and tooling
Search	Pagefind	Static, client-side index
Comments	Giscus	GitHub Discussions

Render pipeline

Quarto writes Hugo-compatible Markdown into content/notebooks/, Hugo builds the site into public/, and Pagefind indexes the generated HTML.

Apache Nutch crawler

Thu, 12 Nov 2026 00:00:00 +0000

A fork of Apache Nutch tuned for web services and data discovery.

DMR++ as a virtual chunk manifest

Thu, 12 Nov 2026 00:00:00 +0000

DMR++ is a metadata sidecar used by OPeNDAP/Hyrax. For an HDF5 granule, it describes the dataset structure and, importantly, the byte ranges of each chunk inside the original file. A client can therefore build a virtual view of the dataset without parsing the granule from scratch.

This notebook makes the mapping explicit with a small synthetic DMR++ document. It then builds a VirtualiZarr ChunkManifest from the same references and compares the result with the shape of an Icechunk-style manifest.

pyLDAvis

Wed, 11 Nov 2026 00:00:00 +0000

A Python port of the R LDAvis package for interactive topic model visualization.

A small numerical check: orbital period from Kepler's third law

Tue, 10 Nov 2026 14:30:00 -0600

Kepler’s third law relates the orbital period $T$ to the semi-major axis $a$ for a body orbiting a mass $M$:

$$ T = 2\pi \sqrt{\frac{a^3}{GM}}. $$

For Earth around the Sun, using $a = 1.496 \times 10^{11}\,\mathrm{m}$ and $GM = 1.327 \times 10^{20}\,\mathrm{m^3\,s^{-2}}$, we expect roughly one year.

import math

GM = 1.32712440018e20
a = 1.495978707e11

period_seconds = 2 * math.pi * math.sqrt(a**3 / GM)
print(period_seconds / (365.25 * 24 * 3600))

1.0000

Reference values

Body	Semi-major axis (AU)	Period (years)
Mercury	0.387	0.241
Earth	1.000	1.000
Mars	1.524	1.881
Jupiter	5.203	11.862

The point is not the arithmetic. The point is that a notebook can carry the claim, the code, and the output together.

filesystem_spec

Tue, 10 Nov 2026 00:00:00 +0000

The shared specification behind Python’s fsspec filesystem implementations.

ipyleaflet

Mon, 09 Nov 2026 00:00:00 +0000

Interactive Leaflet maps inside Jupyter notebooks and JupyterLab.

xarray in a Jupyter notebook

Mon, 09 Nov 2026 00:00:00 +0000

A tiny labeled array

This page starts life as a standard .ipynb file. Quarto executes it and writes Hugo-compatible Markdown, so the output stays readable without a Jupyter server.

import numpy as np
import xarray as xr

da = xr.DataArray(
 np.arange(6).reshape(2, 3),
 dims=("y", "x"),
 coords={"y": [10, 20], "x": [1, 2, 3]},
 name="value",
)
print(da)

<xarray.DataArray 'value' (y: 2, x: 3)> Size: 48B
array([[0, 1, 2],
 [3, 4, 5]])
Coordinates:
 * y (y) int64 16B 10 20
 * x (x) int64 24B 1 2 3

print(f"mean = {da.mean().item():.1f}")

mean = 2.5

earthaccess

Sun, 08 Nov 2026 00:00:00 +0000

Authentication, search, and access for NASA Earth science data collections.

itslive-py

Sat, 07 Nov 2026 00:00:00 +0000

A Python client for discovering and working with ITS_LIVE glacier ice velocity data.

earthcatalog

Fri, 06 Nov 2026 00:00:00 +0000

A GeoParquet-backed STAC catalog for making Earth data collections easier to query and use.

Earth observation data is a software problem

Thu, 05 Nov 2026 09:15:00 -0600

Earth observation archives are often described as data problems. In practice, most of the friction is software: metadata that does not agree with itself, formats that require whole-file downloads, and access patterns that assume a local filesystem.

What cloud-native changes

Chunked, self-describing arrays make partial reads practical. A workflow can open a dataset, inspect coordinates, and request one time slice without downloading the archive.

import xarray as xr

ds = xr.open_zarr(
 "https://example.com/store.zarr",
 consolidated=True,
 chunks={},
)
print(ds)

The hard part is not the API. The hard part is consistency across collections, clear provenance, and clients that fail gracefully.

Cloud-optimized ICESat-2

Thu, 05 Nov 2026 00:00:00 +0000

A project and paper evaluating paged aggregation, chunk sizes, and access patterns for cloud-hosted ICESat-2 HDF5 data.

Joshua Tree National Park

Sat, 17 Oct 2026 09:00:00 -0700

Joshua Tree had been on my bucket list for a while. We finally went a month ago, kept the visit short, and packed in as much desert as we could.

I’ve always liked deserts, and seeing petroglyphs there makes me think that people have been reading this landscape and its skies for a very long time. The night skies were impressive even without a new moon. I got to use my Dwarf 3 telescope again and captured Barnard 33, the Horsehead Nebula. 🌵🌌

About

Mon, 01 Jan 0001 00:00:00 +0000

Hello

I am Luis López (@betolink). I work on open-source scientific software, Earth observation data systems, and reproducible computing.

This site is a personal technical notebook. It collects articles, executable notebooks, project notes, and experiments that are useful enough to write down.

What you will find here

Blog posts about software engineering, Python, data systems, and research software.
Amateur astronomy, mostly dark skies, desert trips, and what I manage to see.
My political views, when I have something worth writing down.
Notebooks rendered with Quarto, including code, plots, equations, and tables.
Projects that I maintain or contribute to.