sciencehub

Use the functions and data of ScienceHub projects from Python.

A ScienceHub project is a marimo notebook and the files beside it. Every function its author wrote as a reusable function (@app.function) can be called from your own code, and every file can be read. Each project page lists them under Functions and Files.

pip install sciencehub

Load a project

import sciencehub as sh

keeling_curve = sh.load("sciencehub-team/keeling-curve")
keeling_curve

sciencehub-team/keeling-curve · Keeling curve
version NS52YCXV, release 1, https://doi.org/10.83371/sh.2610.jd9q4 · https://sciencehub.sh/sciencehub-team/keeling-curve
Monthly CO₂ at Mauna Loa since 1958: NOAA's record and the functions that read it.

Functions
  load_co2(path: str = DATA) -> pd.DataFrame
      Monthly mean CO₂ in the air at Mauna Loa, Hawaii, in ppm, from March 1958.
  yearly_mean(path: str = DATA) -> pd.Series
      The deseasonalized concentration averaged over each complete year, in ppm, by year.
  growth_rate(start_year: int, end_year: int, path: str = DATA) -> float
      Average growth of CO₂ between two complete years, in ppm a year.
  seasonal_cycle(path: str = DATA) -> pd.Series
      Each month's mean departure from the deseasonalized trend, in ppm: the breath of the northern forests.

Files
  data/co2_mm_mlo.csv  38.8 kB
  README.md            1.2 kB

sh.load takes the name from the project's address: "owner/project" for its main notebook, "owner/project/notebook" for another one, or the address itself.

Call a function

help(keeling_curve.growth_rate)
keeling_curve.growth_rate(2015, 2025)   # 2.63

help(), inspect.signature, Jupyter's ? and editor completion show the signature and docstring the author wrote, before anything is downloaded.

The first call downloads the notebook and its files into a cache, imports the notebook, and calls the function on your computer, with the notebook's folder as the working directory: load_co2() finds data/co2_mm_mlo.csv there, as it does on ScienceHub.

The notebook's dependencies have to be installed in your Python. If one is missing, the error names it; keeling_curve.install() installs everything the notebook declares, with pip or uv.

Calling a function runs its author's code, as installing their package would.

Read the data

Any library that reads through fsspec reads a project's files by their sciencehub:// address (sh:// for short): pandas, polars, xarray, Dask and DuckDB among them.

pip install "sciencehub[fsspec]"

import pandas as pd

co2 = pd.read_csv("sciencehub://sciencehub-team/keeling-curve/data/co2_mm_mlo.csv", comment="#")

The address is owner/project[@version]/path: @release-1 reads what release 1's DOI names, @ver_… one saved version. Files are downloaded once and checked against their SHA-256.

The package reads files without fsspec too:

path = keeling_curve.path("data/co2_mm_mlo.csv")   # downloaded once, checked, then read from disk
keeling_curve.download()                            # the notebook and every file, in one folder

Files of public projects also have a plain address any program can read: https://sciencehub.sh/sciencehub-team/keeling-curve/raw/data/co2_mm_mlo.csv.

Pin a version

A load is always one version, and keeling_curve.version says which. Pin it so your results do not change when the author saves a new one:

sh.load("sciencehub-team/keeling-curve", version="ver_01M4V36RH5ZV0RGFPSNS52YCXV")   # one saved version
sh.load("sciencehub-team/keeling-curve", release=1)            # what DOI release 1 names, files included

Private projects

Make a personal access token with the read scope at sciencehub.sh/settings/tokens and set it as SCIENCEHUB_TOKEN, or pass token= to sh.load.

Settings

Apache 2.0.