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[MRG] DOC: OS dependent installation instructions (scikit-learn#15156)
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‎doc/install.rst

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@@ -28,24 +28,99 @@ There are different ways to install scikit-learn:
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Installing the latest release
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=============================
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If you already have a working installation of numpy and scipy,
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the easiest way to install scikit-learn is using ``pip`` or ``conda``.
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.. This quickstart installation is a hack of the awesome
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https://spacy.io/usage/#quickstart page.
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See the original javascript implementation
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https://github.com/ines/quickstart
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.. raw:: html
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<div class="install">
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<strong>Operating System</strong>
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<input type="radio" name="os" id="quickstart-win" checked>
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<label for="quickstart-win">Windows</label>
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<input type="radio" name="os" id="quickstart-mac">
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<label for="quickstart-mac">macOS</label>
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<input type="radio" name="os" id="quickstart-lin">
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<label for="quickstart-lin">Linux</label><br />
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<strong>Packager</strong>
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<input type="radio" name="packager" id="quickstart-pip" checked>
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<label for="quickstart-pip">pip</label>
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<input type="radio" name="packager" id="quickstart-conda">
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<label for="quickstart-conda">conda</label><br />
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<input type="checkbox" name="config" id="quickstart-venv">
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<label for="quickstart-venv"></label>
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</span>
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.. raw:: html
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<div>
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<span class="sk-expandable" data-packager="pip" data-os="windows">Install the 64bit version of Python 3, for instance from <a href="https://www.python.org/">https://www.python.org</a>.</span
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><span class="sk-expandable" data-packager="pip" data-os="mac">Install Python 3 using <a href="https://brew.sh/">homebrew</a> (<code>brew install python</code>) or by manually installing the package from <a href="https://www.python.org">https://www.python.org</a>.</span
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><span class="sk-expandable" data-packager="pip" data-os="linux">Install python3 and python3-pip using the package manager of the Linux Distribution.</span
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><span class="sk-expandable" data-packager="conda"><a href="https://docs.conda.io/projects/conda/en/latest/user-guide/install/">Install conda</a> (no administrator permission required).</span>
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</div>
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Then run:
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.. raw:: html
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<div class="highlight"><pre><code
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><span class="sk-expandable" data-packager="pip" data-os="linux" data-venv="">python3 -m venv sklearn-venv</span
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><span class="sk-expandable" data-packager="pip" data-os="windows" data-venv="">python -m venv sklearn-venv</span
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><span class="sk-expandable" data-packager="pip" data-os="mac" data-venv="">python -m venv sklearn-venv</span
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><span class="sk-expandable" data-packager="pip" data-os="linux" data-venv="">source sklearn-venv/bin/activate</span
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><span class="sk-expandable" data-packager="pip" data-os="mac" data-venv="">source sklearn-venv/bin/activate</span
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><span class="sk-expandable" data-packager="pip" data-os="windows" data-venv="">sklearn-venv\Scripts\activate</span
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><span class="sk-expandable" data-packager="pip" data-venv="">pip install -U scikit-learn</span
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><span class="sk-expandable" data-packager="pip" data-os="mac" data-venv="no">pip install -U scikit-learn</span
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><span class="sk-expandable" data-packager="pip" data-os="windows" data-venv="no">pip install -U scikit-learn</span
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><span class="sk-expandable" data-packager="pip" data-os="linux" data-venv="no">pip3 install -U scikit-learn</span
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><span class="sk-expandable" data-packager="conda" data-venv="">conda create -n sklearn-env</span
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><span class="sk-expandable" data-packager="conda" data-venv="">conda activate sklearn-env</span
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><span class="sk-expandable" data-packager="conda">conda install scikit-learn </span
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></code></pre></div>
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In order to check your installation you can use
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.. raw:: html
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<div class="highlight"><pre><code
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><span class="sk-expandable" data-packager="pip" data-os="linux" data-venv="no">python3 -m pip show scikit-learn # to see which version and where scikit-learn is installed</span
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><span class="sk-expandable" data-packager="pip" data-os="linux" data-venv="no">python3 -m pip freeze # to see all packages installed in the active virtualenv</span
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><span class="sk-expandable" data-packager="pip" data-os="linux" data-venv="no">python3 -c "import sklearn; sklearn.show_versions()"</span
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><span class="sk-expandable" data-packager="pip" data-venv="">python -m pip show scikit-learn # to see which version and where scikit-learn is installed</span
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><span class="sk-expandable" data-packager="pip" data-venv="">python -m pip freeze # to see all packages installed in the active virtualenv</span
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><span class="sk-expandable" data-packager="pip" data-venv="">python -c "import sklearn; sklearn.show_versions()"</span
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><span class="sk-expandable" data-packager="pip" data-os="windows" data-venv="no">python -m pip show scikit-learn # to see which version and where scikit-learn is installed</span
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><span class="sk-expandable" data-packager="pip" data-os="windows" data-venv="no">python -m pip freeze # to see all packages installed in the active virtualenv</span
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><span class="sk-expandable" data-packager="pip" data-os="windows" data-venv="no">python -c "import sklearn; sklearn.show_versions()"</span
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><span class="sk-expandable" data-packager="pip" data-os="mac" data-venv="no">python -m pip show scikit-learn # to see which version and where scikit-learn is installed</span
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><span class="sk-expandable" data-packager="pip" data-os="mac" data-venv="no">python -m pip freeze # to see all packages installed in the active virtualenv</span
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><span class="sk-expandable" data-packager="pip" data-os="mac" data-venv="no">python -c "import sklearn; sklearn.show_versions()"</span
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><span class="sk-expandable" data-packager="conda">conda list scikit-learn # to see which scikit-learn version is installed</span
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><span class="sk-expandable" data-packager="conda">conda list # to see all packages installed in the active conda environment</span
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><span class="sk-expandable" data-packager="conda">python -c "import sklearn; sklearn.show_versions()"</span
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></code></pre></div>
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</div>
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With ``pip``::
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pip install -U scikit-learn
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Note that in order to avoid potential conflicts with other packages it is
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strongly recommended to use a virtual environment, e.g. python3 ``virtualenv``
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(see `python3 virtualenv documentation
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<https://docs.python.org/3/tutorial/venv.html>`_).
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<https://docs.python.org/3/tutorial/venv.html>`_) or `conda environments
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<https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html>`_.
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If you choose to use ``conda`` (see the `instructions for downloading conda
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<https://docs.conda.io/projects/conda/en/latest/user-guide/install/download.html>`_,
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and `how to use conda environments
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<https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html>`_)::
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Using an isolated environment makes possible to install a specific version of
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scikit-learn and its dependencies independently of any previously installed
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Python packages.
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In particular under Linux is it discouraged to install pip packages alongside
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the packages managed by the package manager of the distribution
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(apt, dnf, pacman...).
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conda install scikit-learn
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Note that you should always remember to activate the environment of your choice
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prior to running any Python command whenever you start a new terminal session.
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If you have not installed NumPy or SciPy yet, you can also install these using
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conda or pip. When using pip, please ensure that *binary wheels* are used,
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.. code-block:: none
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# pacman -S python-scikit-learn
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$ sudo pacman -S python-scikit-learn
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Debian/Ubuntu
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Debian distribution).
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Packages can be installed using ``apt-get``::
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$ sudo apt-get install python3-sklearn python3-sklearn-lib
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python3-sklearn-doc
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$ sudo apt-get install python3-sklearn python3-sklearn-lib python3-sklearn-doc
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Fedora
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scikit-learn is available via `pkgsrc-wip
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<http://pkgsrc-wip.sourceforge.net/>`_:
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http://pkgsrc.se/wip/py-scikit_learn
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http://pkgsrc.se/math/py-scikit-learn
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MacPorts for Mac OSX
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It can be installed by typing the following
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command::
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sudo port install py27-scikit-learn
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or::
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sudo port install py36-scikit-learn
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$ sudo port install py36-scikit-learn
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Canopy and Anaconda for all supported platforms

‎doc/themes/scikit-learn-modern/static/css/theme.css

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color: #222;
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background-color: #ecf0f3;
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border-radius: 0.2rem;
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padding: 0.1rem;
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white-space: nowrap;
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}
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color: #808080;
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}
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div.testimonial p {
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color: #1c1c1c;
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}
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/* Installation quickstart */
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/* This quickstart installation is a hack of the awesome
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https://spacy.io/usage/#quickstart page.
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See the original javascript implementation
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https://github.com/ines/quickstart */
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/* style input radio and checkbox */
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div.install > input {
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-moz-appearance: none;
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-webkit-appearance: none;
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appearance: none;
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opacity: 0;
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}
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/* Style the button */
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div.install > label {
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display: inline-block;
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margin-top: 12px;
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padding: 5px 11px;
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background-color: #fff3cd;
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border: none;
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border-radius: 3px;
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color: black;
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}
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div.install > label:hover {
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cursor: pointer;
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}
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/* Style the button when the checkbox is checked */
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div.install > input:checked + label {
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background-color: #ff9c34;
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color: white;
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}
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/* Hide expandable content by default */
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.sk-expandable {
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display: none;
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}
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div.highlight span.sk-expandable:before {
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content: "$ ";
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}
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/* Show hidden content when the checkbox is checked */
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/* for conda */
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#quickstart-conda:checked ~* [data-packager="conda"] {
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display: block;
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}
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#quickstart-conda:checked ~ label[for="quickstart-venv"]:before {
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content: "Use conda environment";
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}
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/* for pip */
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#quickstart-pip:checked ~* [data-packager="pip"] {
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display: block;
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}
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#quickstart-pip:checked ~ label[for="quickstart-venv"]:before {
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content: "Use pip virtualenv";
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}
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#quickstart-win:not(:checked) ~* [data-os="windows"] {
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display: none;
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}
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#quickstart-lin:not(:checked) ~* [data-os="linux"] {
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display: none;
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}
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#quickstart-mac:not(:checked) ~* [data-os="mac"] {
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display: none;
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}
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#quickstart-venv:not(:checked) ~* [data-venv=""] {
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display: none;
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}
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#quickstart-venv:checked ~* [data-venv="no"] {
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display: none;
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}
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/* Algorithm cheet-sheet */
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div.sk-page-content img.map {

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