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Updated pycsep requirements for pip installation & ga using pip (#250)
* ga: added build test from pypi * build: Added Dockerfile for a container installation * ga: reverted branch ga test to upstream ga only * docs: updated and sync'd readme and docs with the installation guide using correct dependencies * updated manifest
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Diff for: ‎.github/workflows/build-test.yml

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@@ -45,3 +45,32 @@ jobs:
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if: matrix.os == 'ubuntu-latest' && matrix.python-version == '3.10'
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run: |
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bash <(curl -s https://codecov.io/bash) || echo 'Codecov failed to upload'
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build_pip:
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if: github.repository == 'SCECcode/pycsep'
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runs-on: ${{ matrix.os }}
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strategy:
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fail-fast: false
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matrix:
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os: [ubuntu-latest]
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python-version: ['3.9']
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defaults:
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run:
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shell: bash -l {0}
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-python@v5
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with:
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python-version: '3.9'
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- name: Install pyCSEP
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run: |
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pip install -e .
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python -c "import csep; print('Version: ', csep.__version__)"
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- name: Test with pytest
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run: |
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pip install vcrpy==4.3.1 pytest pytest-cov
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pytest --cov=./ --cov-config=.coveragerc

Diff for: ‎Dockerfile

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## Build the docker image using:
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# docker build --build-arg USERNAME=$USER --build-arg USER_UID --no-cache -t pycsep .
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## Docker instructions
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# Install Docker image from trusted source
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FROM python:3.9.18-slim-bullseye
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# Setup user id and permissions.
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ARG USERNAME=modeler
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ARG USER_UID=1100
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ARG USER_GID=$USER_UID
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RUN groupadd --non-unique -g $USER_GID $USERNAME \
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&& useradd -u $USER_UID -g $USER_GID -s /bin/sh -m $USERNAME
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# Install git
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RUN apt update
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RUN apt install -y git
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# Set up work directory in the Docker container.
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WORKDIR /usr/src/
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# Set up and create python virtual environment
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ENV VIRTUAL_ENV=/opt/venv
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RUN python3 -m venv $VIRTUAL_ENV
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ENV PATH="$VIRTUAL_ENV/bin:$PATH"
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# Install pycsep.
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RUN git clone https://github.com/SCECcode/pycsep.git
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RUN pip install --no-cache-dir --upgrade pip
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RUN cd pycsep && pip install .
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# Docker can now be initialized as user
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USER $USERNAME
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## Run the docker image in interactive mode from the command line
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# docker run -it --rm --name pycsep pycsep:latest
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Diff for: ‎MANIFEST.in

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include README.md
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include CONTRIBUTING.md
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include CODE_OF_CONDUCT.md
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include Dockerfile
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include LICENSE.txt
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include CHANGELOG.md
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include CREDITS.md

Diff for: ‎README.md

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@@ -36,13 +36,11 @@ pyCSEP can be installed in several ways. It can be installed using conda or pip
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source code found in the pyCSEP github repo. Researchers interested in contributing to pyCSEP development should
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install pyCSEP from source code. pyCSEP depends on the following software packages.
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These which may be installed automatically, or manually, depending on the installation method used.
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* Python 3.7 or later (https://python.org)
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* Python 3.9 or later (https://python.org)
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* NumPy 1.21.3 or later (https://numpy.org)
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* SciPy 1.7.1 or later (https://scipy.org)
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* pandas 1.3.4 or later (https://pandas.pydata.org)
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* cartopy 0.20.0 or later (https://scitools.org.uk/cartopy/docs/latest)
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* GEOS 3.7.2 or later (https://trac.osgeo.org/geos/)
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* PROJ 8.0.0 or later (https://proj.org/)
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* cartopy 0.22.0 or later (https://scitools.org.uk/cartopy/docs/latest)
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Please see the [requirements file](https://github.com/SCECcode/pycsep/blob/master/requirements.yml) for a complete list
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of requirements. These are installed automatically when using the `conda` distribution.

Diff for: ‎docs/getting_started/installing.rst

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If you plan on contributing to this package, visit the
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`contribution guidelines <https://github.com/SCECcode/pycsep/blob/master/CONTRIBUTING.md>`_ for installation instructions.
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.. note:: This package requires >=Python 3.7.
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.. note:: This package requires >=Python 3.9.
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The easiest way to install PyCSEP is using ``conda``. It can also be installed using ``pip`` or built from source.
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should be installed by the installation script. To help manage dependency issues, we recommend using virtual environments
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like `virtualenv`.
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| Python 3.7 or later (https://python.org)
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| Python 3.9 or later (https://python.org)
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|
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| NumPy 1.10 or later (https://numpy.org)
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| NumPy 1.21.3 or later (https://numpy.org)
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| Python package for scientific computing and numerical calculations.
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|
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| GEOS 3.3.3 or later (https://trac.osgeo.org/geos/)
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| C++ library for processing geometry.
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| SciPy 1.7.1 or later (https://scipy.org)
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| Python package that extends NumPy tools.
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|
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| PROJ 4.9.0 or later (https://proj4.org/)
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| Library for cartographic projections.
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Example for Ubuntu: ::
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sudo apt-get install libproj-dev proj-data proj-bin
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sudo apt-get install libgeos-dev
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pip install --upgrade pip
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pip install numpy
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| Pandas 1.3.4 or later (https://pandas.pydata.org)
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| Python package for data analysis and manipulation.
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|
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| Cartopy 0.22.0 or later (https://scitools.org.uk/cartopy/)
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| Python package for geospatial data processing.
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Example for MacOS: ::
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Example for Ubuntu and MacOS: ::
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brew install proj geos
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git clone https://github.com/sceccode/pycsep
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pip install --upgrade pip
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pip install numpy
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pip install -e .
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Installing from Source
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----------------------
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We recommend using virtual environments when installing python packages from source to avoid any dependency conflicts. We prefer
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``conda`` as the package manager over ``pip``, because ``conda`` does a good job of handling binary distributions of packages
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across multiple platforms. Also, we recommend using the ``miniconda`` installer, because it is lightweight and only includes
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across multiple platforms. Also, we recommend using the ``miniconda`` or the ``miniforge`` (which uses mamba for a faster dependency handling) installers, because it is lightweight and only includes
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necessary pacakages like ``pip`` and ``zlib``.
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Using Conda
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***********
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If you don't have ``conda`` on your machine, download and install `Miniconda <https://docs.conda.io/en/latest/miniconda.html>`_. ::
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If you don't have ``conda`` on your machine, download and install `Miniconda <https://docs.conda.io/en/latest/miniconda.html>`_ or `Miniforge <https://github.com/conda-forge/miniforge>`_ ::
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git clone https://github.com/SCECcode/pycsep
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cd pycsep

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