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Backport PR pandas-dev#48220: WEB: Use mambaforge for the getting started installation instructions? (pandas-dev#49211)
Co-authored-by: MarcoGorelli <>
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doc/source/development/contributing_codebase.rst

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@@ -75,6 +75,11 @@ If you want to run checks on all recently committed files on upstream/main you c
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without needing to have done ``pre-commit install`` beforehand.
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.. note::
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You may want to periodically run ``pre-commit gc``, to clean up repos
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which are no longer used.
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.. note::
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If you have conflicting installations of ``virtualenv``, then you may get an

doc/source/development/contributing_environment.rst

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@@ -16,63 +16,8 @@ locally before pushing your changes.
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:local:
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Creating an environment using Docker
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--------------------------------------
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Instead of manually setting up a development environment, you can use `Docker
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<https://docs.docker.com/get-docker/>`_ to automatically create the environment with just several
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commands. pandas provides a ``DockerFile`` in the root directory to build a Docker image
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with a full pandas development environment.
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**Docker Commands**
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Build the Docker image::
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# Build the image pandas-yourname-env
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docker build --tag pandas-yourname-env .
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# Or build the image by passing your GitHub username to use your own fork
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docker build --build-arg gh_username=yourname --tag pandas-yourname-env .
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Run Container::
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# Run a container and bind your local repo to the container
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docker run -it -w /home/pandas --rm -v path-to-local-pandas-repo:/home/pandas pandas-yourname-env
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Then a ``pandas-dev`` virtual environment will be available with all the development dependencies.
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.. code-block:: shell
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root@... :/home/pandas# conda env list
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# conda environments:
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#
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base * /opt/conda
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pandas-dev /opt/conda/envs/pandas-dev
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.. note::
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If you bind your local repo for the first time, you have to build the C extensions afterwards.
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Run the following command inside the container::
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python setup.py build_ext -j 4
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You need to rebuild the C extensions anytime the Cython code in ``pandas/_libs`` changes.
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This most frequently occurs when changing or merging branches.
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*Even easier, you can integrate Docker with the following IDEs:*
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**Visual Studio Code**
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You can use the DockerFile to launch a remote session with Visual Studio Code,
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a popular free IDE, using the ``.devcontainer.json`` file.
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See https://code.visualstudio.com/docs/remote/containers for details.
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**PyCharm (Professional)**
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Enable Docker support and use the Services tool window to build and manage images as well as
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run and interact with containers.
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See https://www.jetbrains.com/help/pycharm/docker.html for details.
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Creating an environment without Docker
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---------------------------------------
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Option 1: creating an environment without Docker
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------------------------------------------------
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Installing a C compiler
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~~~~~~~~~~~~~~~~~~~~~~~
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extensions, which means you need a C compiler. This process depends on which
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platform you're using.
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If you have setup your environment using ``conda``, the packages ``c-compiler``
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If you have setup your environment using :ref:`mamba <contributing.mamba>`, the packages ``c-compiler``
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and ``cxx-compiler`` will install a fitting compiler for your platform that is
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compatible with the remaining conda packages. On Windows and macOS, you will
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compatible with the remaining mamba packages. On Windows and macOS, you will
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also need to install the SDKs as they have to be distributed separately.
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These packages will automatically be installed by using the ``pandas``
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``environment.yml`` file.
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**macOS**
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To use the ``conda``-based compilers, you will need to install the
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To use the :ref:`mamba <contributing.mamba>`-based compilers, you will need to install the
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Developer Tools using ``xcode-select --install``. Otherwise
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information about compiler installation can be found here:
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https://devguide.python.org/setup/#macos
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**Linux**
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For Linux-based ``conda`` installations, you won't have to install any
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additional components outside of the conda environment. The instructions
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below are only needed if your setup isn't based on conda environments.
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For Linux-based :ref:`mamba <contributing.mamba>` installations, you won't have to install any
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additional components outside of the mamba environment. The instructions
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below are only needed if your setup isn't based on mamba environments.
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Some Linux distributions will come with a pre-installed C compiler. To find out
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which compilers (and versions) are installed on your system::
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Let us know if you have any difficulties by opening an issue or reaching out on our contributor
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community :ref:`Slack <community.slack>`.
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Creating a Python environment
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. _contributing.mamba:
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Option 1a: using mamba (recommended)
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Now create an isolated pandas development environment:
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* Install either `Anaconda <https://www.anaconda.com/products/individual>`_, `miniconda
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<https://docs.conda.io/en/latest/miniconda.html>`_, or `miniforge <https://github.com/conda-forge/miniforge>`_
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* Make sure your conda is up to date (``conda update conda``)
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* Install `mamba <https://mamba.readthedocs.io/en/latest/installation.html>`_
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* Make sure your mamba is up to date (``mamba update mamba``)
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* Make sure that you have :any:`cloned the repository <contributing.forking>`
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* ``cd`` to the pandas source directory
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.. code-block:: none
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# Create and activate the build environment
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conda env create -f environment.yml
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conda activate pandas-dev
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# or with older versions of Anaconda:
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source activate pandas-dev
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mamba env create
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mamba activate pandas-dev
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# Build and install pandas
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python setup.py build_ext -j 4
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$ python
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>>> import pandas
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>>> print(pandas.__version__)
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0.22.0.dev0+29.g4ad6d4d74
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>>> print(pandas.__version__) # note: the exact output may differ
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1.5.0.dev0+1355.ge65a30e3eb.dirty
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This will create the new environment, and not touch any of your existing environments,
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nor any existing Python installation.
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To view your environments::
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conda info -e
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To return to your root environment::
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conda deactivate
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See the full conda docs `here <https://conda.io/projects/conda/en/latest/>`__.
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mamba deactivate
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Option 1b: using pip
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~~~~~~~~~~~~~~~~~~~~
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Creating a Python environment (pip)
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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If you aren't using conda for your development environment, follow these instructions.
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If you aren't using mamba for your development environment, follow these instructions.
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You'll need to have at least the :ref:`minimum Python version <install.version>` that pandas supports.
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You also need to have ``setuptools`` 51.0.0 or later to build pandas.
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Below is a brief overview on how to set-up a virtual environment with Powershell
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under Windows. For details please refer to the
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`official virtualenv user guide <https://virtualenv.pypa.io/en/latest/user_guide.html#activators>`__
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`official virtualenv user guide <https://virtualenv.pypa.io/en/latest/user_guide.html#activators>`__.
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Use an ENV_DIR of your choice. We'll use ~\\virtualenvs\\pandas-dev where
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'~' is the folder pointed to by either $env:USERPROFILE (Powershell) or
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# Build and install pandas
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python setup.py build_ext -j 4
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python -m pip install -e . --no-build-isolation --no-use-pep517
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Option 2: creating an environment using Docker
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----------------------------------------------
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Instead of manually setting up a development environment, you can use `Docker
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<https://docs.docker.com/get-docker/>`_ to automatically create the environment with just several
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commands. pandas provides a ``DockerFile`` in the root directory to build a Docker image
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with a full pandas development environment.
226+
227+
**Docker Commands**
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Build the Docker image::
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# Build the image pandas-yourname-env
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docker build --tag pandas-yourname-env .
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# Or build the image by passing your GitHub username to use your own fork
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docker build --build-arg gh_username=yourname --tag pandas-yourname-env .
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Run Container::
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# Run a container and bind your local repo to the container
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docker run -it -w /home/pandas --rm -v path-to-local-pandas-repo:/home/pandas pandas-yourname-env
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Then a ``pandas-dev`` virtual environment will be available with all the development dependencies.
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.. code-block:: shell
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root@... :/home/pandas# conda env list
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# conda environments:
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#
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base * /opt/conda
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pandas-dev /opt/conda/envs/pandas-dev
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.. note::
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If you bind your local repo for the first time, you have to build the C extensions afterwards.
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Run the following command inside the container::
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python setup.py build_ext -j 4
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257+
You need to rebuild the C extensions anytime the Cython code in ``pandas/_libs`` changes.
258+
This most frequently occurs when changing or merging branches.
259+
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*Even easier, you can integrate Docker with the following IDEs:*
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**Visual Studio Code**
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264+
You can use the DockerFile to launch a remote session with Visual Studio Code,
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a popular free IDE, using the ``.devcontainer.json`` file.
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See https://code.visualstudio.com/docs/remote/containers for details.
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**PyCharm (Professional)**
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Enable Docker support and use the Services tool window to build and manage images as well as
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run and interact with containers.
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See https://www.jetbrains.com/help/pycharm/docker.html for details.

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