**********************************************
Welcome to The REsource eXtraction (rex) tool!
**********************************************
|Docs| |Tests| |Linter| |PyPi| |PythonV| |Conda| |Licence| |CodeCov| |Zeonodo|
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.. inclusion-intro
What is rex?
=============
``rex`` stands for **REsource eXtraciton** tool.
``rex`` enables the efficient and scalable extraction, manipulation, and
computation with NRELs flagship renewable resource datasets such as: the Wind
Integration National Dataset (WIND Toolkit), the National Solar Radiation
Database (NSRDB), the Ocean Surface Wave Hindcast (US Wave) Data, and the
High-resolution downscaled climate change data (Sup3rCC).
To get started accessing NREL's datasets, see the primer on `NREL Renewable
Energy Resource Data
<https://nrel.github.io/rex/misc/examples.nrel_data.html>`_ or the
`installation instructions <https://nrel.github.io/rex/#installing-rex>`_.
You might also want to check out the basic `Resource Class
<https://nrel.github.io/rex/_autosummary/rex.resource.Resource.html>`_ that
can be used to efficiently query NREL data, or our various `example use cases
<https://nrel.github.io/rex/misc/examples.html>`_.
Installing rex
==============
NOTE: The installation instruction below assume that you have python installed
on your machine and are using `conda <https://docs.conda.io/en/latest/index.html>`_
as your package/environment manager.
Option 1: Install from PIP or Conda (recommended for analysts):
---------------------------------------------------------------
1. Create a new environment:
``conda create --name rex``
2. Activate directory:
``conda activate rex``
3. Basic ``rex`` install:
1) ``pip install NREL-rex``
2) or ``conda install nrel-rex --channel=nrel``
4. Install for users outside of NREL that want to access data via HSDS or S3 as per the instructions `here <https://nrel.github.io/rex/misc/examples.nrel_data.html#data-location-external-users>`_:
1) ``pip install NREL-rex[s3]`` for easy no-setup direct access of the data on S3 via ``fsspec`` as per `this s3 example <https://nrel.github.io/rex/misc/examples.fsspec.html>`_
2) or ``pip install NREL-rex[hsds]`` for more performant access of the data on HSDS with slightly more setup as per `this hsds example <https://nrel.github.io/rex/misc/examples.hsds.html>`_
Option 2: Clone repo (recommended for developers)
-------------------------------------------------
1. from home dir, ``git clone git@github.com:NREL/rex.git``
2. Create ``rex`` environment and install package
1) Create a conda env: ``conda create -n rex``
2) Run the command: ``conda activate rex``
3) cd into the repo cloned in 1.
4) prior to running ``pip`` below, make sure the branch is correct (install
from main!)
5) Install ``rex`` and its dependencies by running:
``pip install .`` (or ``pip install -e .`` if running a dev branch
or working on the source code)
3. Check that ``rex`` was installed successfully
1) From any directory, run the following commands. This should return the
help pages for the CLI's.
- ``rex``
- ``NSRDBX``
- ``WINDX``
- ``US-wave``
rex command line tools
======================
- `rex <https://nrel.github.io/rex/_cli/rex.html#rex>`_
- `NSRDBX <https://nrel.github.io/rex/_cli/NSRDBX.html#NSRDBX>`_
- `WINDX <https://nrel.github.io/rex/_cli/WINDX.html#WINDX>`_
- `US-wave <https://nrel.github.io/rex/_cli/US-wave.html#US-wave>`_
- `WaveX <https://nrel.github.io/rex/_cli/WaveX.html#Wavex>`_
- `MultiYearX <https://nrel.github.io/rex/_cli/MultiYearX.html#MultiYearX>`_
- `rechunk <https://nrel.github.io/rex/_cli/rechunk.html#rechunk>`_
- `temporal-stats <https://nrel.github.io/rex/_cli/temporal-stats.html#temporal-stats>`_
- `wind-rose <https://nrel.github.io/rex/_cli/wind-rose.html#wind-rose>`_
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"description": "**********************************************\nWelcome to The REsource eXtraction (rex) tool!\n**********************************************\n\n|Docs| |Tests| |Linter| |PyPi| |PythonV| |Conda| |Licence| |CodeCov| |Zeonodo|\n\n.. |Docs| image:: https://github.com/NREL/rex/workflows/Documentation/badge.svg\n :target: https://nrel.github.io/rex/\n\n.. |Tests| image:: https://github.com/NREL/rex/workflows/Pytests/badge.svg\n :target: https://github.com/NREL/rex/actions?query=workflow%3A%22Pytests%22\n\n.. |Linter| image:: https://github.com/NREL/rex/workflows/Lint%20Code%20Base/badge.svg\n :target: https://github.com/NREL/rex/actions?query=workflow%3A%22Lint+Code+Base%22\n\n.. |PyPi| image:: https://img.shields.io/pypi/pyversions/NREL-rex.svg\n :target: https://pypi.org/project/NREL-rex/\n\n.. |PythonV| image:: https://badge.fury.io/py/NREL-rex.svg\n :target: https://badge.fury.io/py/NREL-rex\n\n.. |Conda| image:: https://anaconda.org/nrel/nrel-rex/badges/version.svg\n :target: https://anaconda.org/nrel/nrel-rex\n\n.. |Licence| image:: https://anaconda.org/nrel/nrel-rex/badges/license.svg\n :target: https://anaconda.org/nrel/nrel-rex\n\n.. |CodeCov| image:: https://codecov.io/gh/nrel/rex/branch/main/graph/badge.svg?token=WQ95L11SRS\n :target: https://codecov.io/gh/nrel/rex\n\n.. |Zeonodo| image:: https://zenodo.org/badge/253541811.svg\n :target: https://zenodo.org/badge/latestdoi/253541811\n\n.. inclusion-intro\n\nWhat is rex?\n=============\n``rex`` stands for **REsource eXtraciton** tool.\n\n``rex`` enables the efficient and scalable extraction, manipulation, and\ncomputation with NRELs flagship renewable resource datasets such as: the Wind\nIntegration National Dataset (WIND Toolkit), the National Solar Radiation\nDatabase (NSRDB), the Ocean Surface Wave Hindcast (US Wave) Data, and the\nHigh-resolution downscaled climate change data (Sup3rCC).\n\nTo get started accessing NREL's datasets, see the primer on `NREL Renewable\nEnergy Resource Data\n<https://nrel.github.io/rex/misc/examples.nrel_data.html>`_ or the\n`installation instructions <https://nrel.github.io/rex/#installing-rex>`_.\n\nYou might also want to check out the basic `Resource Class\n<https://nrel.github.io/rex/_autosummary/rex.resource.Resource.html>`_ that\ncan be used to efficiently query NREL data, or our various `example use cases\n<https://nrel.github.io/rex/misc/examples.html>`_.\n\nInstalling rex\n==============\n\nNOTE: The installation instruction below assume that you have python installed\non your machine and are using `conda <https://docs.conda.io/en/latest/index.html>`_\nas your package/environment manager.\n\nOption 1: Install from PIP or Conda (recommended for analysts):\n---------------------------------------------------------------\n\n1. Create a new environment:\n ``conda create --name rex``\n\n2. Activate directory:\n ``conda activate rex``\n\n3. Basic ``rex`` install:\n 1) ``pip install NREL-rex``\n 2) or ``conda install nrel-rex --channel=nrel``\n\n4. Install for users outside of NREL that want to access data via HSDS or S3 as per the instructions `here <https://nrel.github.io/rex/misc/examples.nrel_data.html#data-location-external-users>`_:\n 1) ``pip install NREL-rex[s3]`` for easy no-setup direct access of the data on S3 via ``fsspec`` as per `this s3 example <https://nrel.github.io/rex/misc/examples.fsspec.html>`_\n 2) or ``pip install NREL-rex[hsds]`` for more performant access of the data on HSDS with slightly more setup as per `this hsds example <https://nrel.github.io/rex/misc/examples.hsds.html>`_\n\nOption 2: Clone repo (recommended for developers)\n-------------------------------------------------\n\n1. from home dir, ``git clone git@github.com:NREL/rex.git``\n\n2. Create ``rex`` environment and install package\n 1) Create a conda env: ``conda create -n rex``\n 2) Run the command: ``conda activate rex``\n 3) cd into the repo cloned in 1.\n 4) prior to running ``pip`` below, make sure the branch is correct (install\n from main!)\n 5) Install ``rex`` and its dependencies by running:\n ``pip install .`` (or ``pip install -e .`` if running a dev branch\n or working on the source code)\n\n3. Check that ``rex`` was installed successfully\n 1) From any directory, run the following commands. 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