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Copy file name to clipboardexpand all lines: _sources/getting_started/developers.rst.txt
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Development Dependencies
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~~~~~~~~~~~~~~~~~~~~~~~~
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Building the package from source additionally requires the following dependencies:
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* cython (>=3.0a4)
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We also use pre-commit hooks to identify simple issues before submission.
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To install these dependencies, run::
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Setting Up Your Environment
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~~~~~~~~~~~~~~~~~~~~~~~~~~~
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To contribute to the `quantile-forest` source code, start by forking and then cloning the repository (i.e. `git clone [email protected]:YourUsername/quantile-forest.git`).
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Once inside the repository, you can prepare a development environment. Using conda::
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pip install cython pre-commit
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conda create -n qf python=3.12
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conda activate qf
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conda install pre-commit
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pre-commit install
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Development Installation
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~~~~~~~~~~~~~~~~~~~~~~~~
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Ensure that `pytest` and `pytest-cov` are installed::
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$ pip install pytest pytest-cov
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pip install pytest pytest-cov
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To test the code::
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$ python -m pytest quantile_forest -v
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python -m pytest quantile_forest -v
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To test the code and produce a coverage report::
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$ python -m pytest quantile_forest --cov-report html --cov=quantile_forest
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python -m pytest quantile_forest --cov-report html --cov=quantile_forest
<dt><strong>estimator_</strong><spanclass="classifier"><aclass="reference external" href="https://scikit-learn.org/stable/modules/generated/sklearn.tree.ExtraTreeRegressor.html#sklearn.tree.ExtraTreeRegressor" title="(in scikit-learn v1.5)"><codeclass="xref py py-class docutils literal notranslate"><spanclass="pre">ExtraTreeRegressor</span></code></a></span></dt><dd><p>The child estimator template used to create the collection of fitted
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sub-estimators.</p>
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<divclass="versionadded">
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<p><spanclass="versionmodified added">New in scikit-learn version 1.2: </span><codeclass="docutils literal notranslate"><spanclass="pre">base_estimator_</span></code> was renamed to <codeclass="docutils literal notranslate"><spanclass="pre">estimator_</span></code>.</p>
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</div>
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</dd>
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<dt><strong>estimators_</strong><spanclass="classifier">list of DecisionTreeRegressor</span></dt><dd><p>The collection of fitted sub-estimators.</p>
<dt><strong>estimator_</strong><spanclass="classifier"><aclass="reference external" href="https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeRegressor.html#sklearn.tree.DecisionTreeRegressor" title="(in scikit-learn v1.5)"><codeclass="xref py py-class docutils literal notranslate"><spanclass="pre">DecisionTreeRegressor</span></code></a></span></dt><dd><p>The child estimator template used to create the collection of fitted
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sub-estimators.</p>
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<divclass="versionadded">
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<p><spanclass="versionmodified added">New in scikit-learn version 1.2: </span><codeclass="docutils literal notranslate"><spanclass="pre">base_estimator_</span></code> was renamed to <codeclass="docutils literal notranslate"><spanclass="pre">estimator_</span></code>.</p>
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</div>
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</dd>
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<dt><strong>estimators_</strong><spanclass="classifier">list of DecisionTreeRegressor</span></dt><dd><p>The collection of fitted sub-estimators.</p>
<h2>Setting Up Your Environment<aclass="headerlink" href="#setting-up-your-environment" title="Link to this heading">#</a></h2>
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<p>To contribute to the <codeclass="docutils literal notranslate"><spanclass="pre">quantile-forest</span></code> source code, start by forking and then cloning the repository (i.e. <codeclass="docutils literal notranslate"><spanclass="pre">git</span><spanclass="pre">clone</span><spanclass="pre">git@github.com:YourUsername/quantile-forest.git</span></code>).</p>
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<p>Once inside the repository, you can prepare a development environment. Using conda:</p>
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<sectionid="test-and-coverage">
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<h2>Test and Coverage<aclass="headerlink" href="#test-and-coverage" title="Link to this heading">#</a></h2>
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<p>Ensure that <codeclass="docutils literal notranslate"><spanclass="pre">pytest</span></code> and <codeclass="docutils literal notranslate"><spanclass="pre">pytest-cov</span></code> are installed:</p>
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