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add conda-forge instructions to installation.md
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docs/installation.md

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There are different ways to install MDIO:
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- Install the latest release.
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- Building package from source.
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- Install the latest release via [`pip`](#using-pip-and-virtualenv) or [`conda`](#using-conda).
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- Building package [from source](#building-from-source).
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```{note}
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We strongly recommend using a virtual environment `venv` or `conda`
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Install the 64-bit version of Python 3 from https://www.python.org.
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Then we can create a `venv` and install _MDIO_.
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```shell
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$ python -m venv mdio-venv
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$ mdio-venv/Scripts/activate
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$ pip install -U multidimio
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```
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To check if installation was successful see [checking installation](#checking-installation).
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You can also install some optional dependencies (extras) like this:
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```shell
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$ pip install multidimio[distributed]
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$ pip install multidimio[cloud]
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$ pip install multidimio[lossy]
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```
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`distributed` installs [Dask][dask] for parallel, distributed processing.\
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`cloud` installs [fsspec][fsspec] backed I/O libraries for [AWS' S3][s3fs],
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[Google's GCS][gcsfs], and [Azure ABS][adlfs].\
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`lossy` will install the [ZFPY][zfp] library for lossy chunk compression.
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[dask]: https://www.dask.org/
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[fsspec]: https://filesystem-spec.readthedocs.io/en/latest/
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[s3fs]: https://s3fs.readthedocs.io/
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[gcsfs]: https://gcsfs.readthedocs.io/
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[adlfs]: https://github.com/fsspec/adlfs
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[zfp]: https://computing.llnl.gov/projects/zfp
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## Using `conda`
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MDIO can also be installed in a `conda` environment.
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```{warning}
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Native `conda` installation for MDIO is work-in-progress. Due to the bundled
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packages with the [Anaconda](https://www.anaconda.com/products/distribution)
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distrtibution, installing MDIO using `pip` into the `conda` environment will
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cause your environment to break.
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In the meantime, please use the
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[Miniconda](https://docs.conda.io/en/latest/miniconda.html) distribution which
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doesn't come with bundled packages.
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```{note}
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_MDIO_ is hosted in the `conda-forge` channel. Make sure to always provide the
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`-c conda-forge` when running `conda install` or else it won't be able to find
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the package.
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```
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We first run the following to create and activate an environment:
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$ conda activate mdio-env
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```
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Then we need to install with `pip`:
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Then we can to install with `conda`:
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```shell
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$ pip install -U multidimio
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$ conda install -c conda-forge multidimio
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```
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The above command will install MDIO into your `conda` environment.
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```{note}
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_MDIO_ extras must be installed separately when using `conda`.
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```
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## Checking Installation
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After installing MDIO, run the following:
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You should see the version of MDIO printed to the screen.
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## Extras
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## Building from Source
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You can also install some optional dependencies (extras) like this:
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All dependencies of _MDIO_ are Python packages, so the build process is very simple.
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To install from source, we need to clone the repo first and then install locally via `pip`.
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```shell
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$ pip install multidimio[distributed]
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$ pip install multidimio[cloud]
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$ pip install multidimio[lossy]
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$ git clone https://github.com/TGSAI/mdio-python.git
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$ cd mdio-python
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$ pip install .
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```
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`distributed` installs [Dask][dask] for parallel, distributed processing.\
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`cloud` installs [fsspec][fsspec] backed I/O libraries for [AWS' S3][s3fs],
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[Google's GCS][gcsfs], and [Azure ABS][adlfs].\
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`lossy` will install the [ZFPY][zfp] library for lossy chunk compression.
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We can also install the extras in a similar way, for example:
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[dask]: https://www.dask.org/
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[fsspec]: https://filesystem-spec.readthedocs.io/en/latest/
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[s3fs]: https://s3fs.readthedocs.io/
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[gcsfs]: https://gcsfs.readthedocs.io/
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[adlfs]: https://github.com/fsspec/adlfs
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[zfp]: https://computing.llnl.gov/projects/zfp
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```shell
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$ pip install .[cloud]
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```
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If you want an editable version of _MDIO_ then we could install it with the command below.
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This does allow you to make code changes on the fly.
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```shell
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$ pip install --editable .[cloud]
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```
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To check if installation was successful see [checking installation](#checking-installation).

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