Metadata-Version: 2.1
Name: intake-coops
Version: 0.1.0
Summary: Intake interface to NOAA CO-OPS data
Home-page: https://github.com/axiom-data-science/intake-coops
Author: Axiom Data Science
Author-email: kthyng@axds.co
License: MIT
Classifier: Development Status :: 5 - Production/Stable
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE.txt

intake-coops
==============================

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Intake interface to NOAA CO-OPS data

Uses the [`noaa_coops`](https://github.com/GClunies/noaa_coops) package to read in NOAA CO-OPS data.

Currently limited to currents only with limited selections. Returns an `xarray` Dataset, but there are `intake` Sources for both `DataFrame` and `xarray`.

--------

<p><small>Project based on the <a target="_blank" href="https://github.com/jbusecke/cookiecutter-science-project">cookiecutter science project template</a>.</small></p>


# Installation

Clone from github (HTTPS or SSH)

    >>> git clone https://github.com/axiom-data-science/intake-coops.git

Install environment file

    >>> conda env create -f environment.yml

Activate new environment

    >>> conda activate intake-coops

Install package locally in package directory

    >>> pip install -e .


# Example Usage

If you input to `intake.open_coops_cat()` the keyword argument `process_adcp=True`, the ADCP Dataset will contain velocity on u and v components, along- and across-channel components, and along- and across-channel subtidal signal (processed with pl33 tidal filter, also included).

```
import intake

stations = ["COI0302", "COI0512"]
cat = intake.open_coops_cat(stations)

# sources in catalog
print(list(cat))

# look at a source
print(cat["COI0302"])

# read in data to a Dataset
ds = cat["COI0302"].read()
```


### Development

To also develop this package, install additional packages with:
``` bash
$ conda install --file requirements-dev.txt
```

To then check code before committing and pushing it to github, locally run
``` bash
$ pre-commit run --all-files
```
