pyo_oracle¶

Python client for the Bio-ORACLE ERDDAP server.

pyo_oracle lets you discover, inspect, subset, download, and load Bio-ORACLE marine environmental layers (temperature, salinity, nutrients, sea ice, and more) straight from Python. It is the Python counterpart of the R package biooracler and is built on top of erddapy.

Features¶

List & filter layers by free-text search, variable, SSP scenario, time period, and depth.
Inspect a layer's dimension ranges and variables with info_layer.
Subset easily with build_constraints — no hand-written constraint dicts.
Download to NetCDF/CSV files, optionally restricting to a subset of variables.
Load into memory as a pandas.DataFrame or xarray.Dataset with load_layer.

Installation¶

# With pip
pip install pyo-oracle

# Load layers as xarray (optional extra)
pip install "pyo-oracle[xarray]"

# With conda
conda create -n pyo_oracle conda-forge::pyo-oracle

Quick example¶

import pyo_oracle as pyo

# Discover layers
pyo.list_layers(search="Temperature")

# Inspect one
pyo.info_layer("thetao_baseline_2000_2019_depthsurf")

# Build constraints and load into memory
constraints = pyo.build_constraints(
    "thetao_baseline_2000_2019_depthsurf",
    latitude=(0, 10),
    longitude=(0, 10),
)
df = pyo.load_layer(
    "thetao_baseline_2000_2019_depthsurf",
    constraints=constraints,
    variables=["thetao_mean"],
)

See the Quickstart and Tutorials to go further.