Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

AWS NOAA WHOI #221

Merged
merged 7 commits into from
Dec 13, 2022
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
22 changes: 22 additions & 0 deletions recipes/aws-noaa-whoi/meta.yaml
Original file line number Diff line number Diff line change
@@ -0,0 +1,22 @@
title: 'AWS NOAA WHOI SST'
description: 'Analysis-ready datasets derived from AWS NOAA WHOI NetCDF'
pangeo_forge_version: '0.9.2'
pangeo_notebook_version: '2021.07.17'
recipes:
- id: aws-noaa-sea-surface-temp-whoi
object: 'recipe:recipe'
provenance:
providers:
- name: 'AWS NOAA Oceanic CDR'
description: 'Registry of Open Data on AWS National Oceanographic & Atmospheric Administration National Centers for Environmental Information'
roles:
- producer
- licensor
url: s3://noaa-cdr-sea-surface-temp-whoi-pds/
license: 'Open Data'
maintainers:
- name: 'Kathryn Berger'
orcid: '0000-0001-9731-6519'
github: kathrynberger
bakery:
id: 'pangeo-ldeo-nsf-earthcube'
29 changes: 29 additions & 0 deletions recipes/aws-noaa-whoi/recipe.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,29 @@
import os
from os.path import join

import s3fs

from pangeo_forge_recipes.patterns import pattern_from_file_sequence
from pangeo_forge_recipes.recipes.reference_hdf_zarr import HDFReferenceRecipe

url_base = 's3://noaa-cdr-sea-surface-temp-whoi-pds/data/'

file_list = []
fs = s3fs.S3FileSystem(anon=True)


def is_nc(x):
return x.endswith('.nc')


def add_s3(x):
return 's3://' + x


years_folders = fs.ls(join(url_base))
years = list(map(lambda x: os.path.basename(x), years_folders))

for year in years:
file_list += sorted(filter(is_nc, map(add_s3, fs.ls(join(url_base, str(year)), detail=False))))
pattern = pattern_from_file_sequence(file_list, 'time', nitems_per_file=1)
recipe = HDFReferenceRecipe(pattern, netcdf_storage_options={'anon': True})