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Merge pull request #453 from openml/develop
Prepare new release
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‎.gitignore‎

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*~
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doc/generated
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examples/.ipynb_checkpoints
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# Byte-compiled / optimized / DLL files

‎CONTRIBUTING.md‎

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How to contribute
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-----------------
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The preferred workflow for contributing to the OpenML python connector is to
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fork the [main repository](https://github.com/openml/openml-python) on
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GitHub, clone, check out the branch `develop`, and develop on a new branch
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branch. Steps:
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1. Fork the [project repository](https://github.com/openml/openml-python)
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by clicking on the 'Fork' button near the top right of the page. This creates
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a copy of the code under your GitHub user account. For more details on
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how to fork a repository see [this guide](https://help.github.com/articles/fork-a-repo/).
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2. Clone your fork of the openml-python repo from your GitHub account to your
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local disk:
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```bash
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$ git clone git@github.com:YourLogin/openml-python.git
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$ cd openml-python
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```
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3. Swith to the ``develop`` branch:
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```bash
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$ git checkout develop
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```
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3. Create a ``feature`` branch to hold your development changes:
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```bash
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$ git checkout -b feature/my-feature
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```
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Always use a ``feature`` branch. It's good practice to never work on the ``master`` or ``develop`` branch! To make the nature of your pull request easily visible, please perpend the name of the branch with the type of changes you want to merge, such as ``feature`` if it contains a new feature, ``fix`` for a bugfix, ``doc`` for documentation and ``maint`` for other maintenance on the package.
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4. Develop the feature on your feature branch. Add changed files using ``git add`` and then ``git commit`` files:
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```bash
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$ git add modified_files
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$ git commit
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```
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to record your changes in Git, then push the changes to your GitHub account with:
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```bash
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$ git push -u origin my-feature
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```
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5. Follow [these instructions](https://help.github.com/articles/creating-a-pull-request-from-a-fork)
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to create a pull request from your fork. This will send an email to the committers.
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(If any of the above seems like magic to you, please look up the
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[Git documentation](https://git-scm.com/documentation) on the web, or ask a friend or another contributor for help.)
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Pull Request Checklist
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----------------------
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We recommended that your contribution complies with the
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following rules before you submit a pull request:
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- Follow the
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[pep8 style guilde](https://www.python.org/dev/peps/pep-0008/).
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- If your pull request addresses an issue, please use the pull request title
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to describe the issue and mention the issue number in the pull request description. This will make sure a link back to the original issue is
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created.
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- An incomplete contribution -- where you expect to do more work before
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receiving a full review -- should be prefixed `[WIP]` (to indicate a work
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in progress) and changed to `[MRG]` when it matures. WIPs may be useful
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to: indicate you are working on something to avoid duplicated work,
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request broad review of functionality or API, or seek collaborators.
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WIPs often benefit from the inclusion of a
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[task list](https://github.com/blog/1375-task-lists-in-gfm-issues-pulls-comments)
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in the PR description.
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- All tests pass when running `nosetests`. On
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Unix-like systems, check with (from the toplevel source folder):
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```bash
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$ nosetests
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```
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For Windows systems, execute the command from an Anaconda Prompt or add `nosetests` to PATH before executing the command.
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- Documentation and high-coverage tests are necessary for enhancements to be
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accepted. Bug-fixes or new features should be provided with
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[non-regression tests](https://en.wikipedia.org/wiki/Non-regression_testing).
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These tests verify the correct behavior of the fix or feature. In this
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manner, further modifications on the code base are granted to be consistent
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with the desired behavior.
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For the Bug-fixes case, at the time of the PR, this tests should fail for
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the code base in develop and pass for the PR code.
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You can also check for common programming errors with the following
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tools:
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- Code with good unittest **coverage** (at least 80%), check with:
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```bash
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$ pip install nose coverage
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$ nosetests --with-coverage path/to/tests_for_package
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```
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- No pyflakes warnings, check with:
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```bash
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$ pip install pyflakes
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$ pyflakes path/to/module.py
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```
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- No PEP8 warnings, check with:
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```bash
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$ pip install pep8
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$ pep8 path/to/module.py
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```
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Filing bugs
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-----------
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We use GitHub issues to track all bugs and feature requests; feel free to
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open an issue if you have found a bug or wish to see a feature implemented.
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It is recommended to check that your issue complies with the
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following rules before submitting:
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- Verify that your issue is not being currently addressed by other
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[issues](https://github.com/openml/openml-python/issues)
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or [pull requests](https://github.com/openml/openml-python/pulls).
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- Please ensure all code snippets and error messages are formatted in
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appropriate code blocks.
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See [Creating and highlighting code blocks](https://help.github.com/articles/creating-and-highlighting-code-blocks).
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- Please include your operating system type and version number, as well
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as your Python, openml, scikit-learn, numpy, and scipy versions. This information
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can be found by running the following code snippet:
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```python
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import platform; print(platform.platform())
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import sys; print("Python", sys.version)
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import numpy; print("NumPy", numpy.__version__)
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import scipy; print("SciPy", scipy.__version__)
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import sklearn; print("Scikit-Learn", sklearn.__version__)
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import openml; print("OpenML", openml.__version__)
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```
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New contributor tips
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--------------------
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A great way to start contributing to scikit-learn is to pick an item
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from the list of [Easy issues](https://github.com/openml/openml-python/issues?q=label%3Aeasy)
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in the issue tracker. Resolving these issues allow you to start
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contributing to the project without much prior knowledge. Your
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assistance in this area will be greatly appreciated by the more
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experienced developers as it helps free up their time to concentrate on
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other issues.
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Documentation
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-------------
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We are glad to accept any sort of documentation: function docstrings,
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reStructuredText documents (like this one), tutorials, etc.
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reStructuredText documents live in the source code repository under the
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doc/ directory.
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You can edit the documentation using any text editor and then generate
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the HTML output by typing ``make html`` from the doc/ directory.
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The resulting HTML files will be placed in ``build/html/`` and are viewable in
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a web browser. See the ``README`` file in the ``doc/`` directory for more
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information.
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For building the documentation, you will need
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[sphinx](http://sphinx.pocoo.org/),
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[matplotlib](http://matplotlib.org/), and
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[pillow](http://pillow.readthedocs.io/en/latest/).
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[sphinx-bootstrap-theme](https://ryan-roemer.github.io/sphinx-bootstrap-theme/)

‎ISSUE_TEMPLATE.md‎

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#### Description
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<!-- Example: Joblib Error thrown when calling fit on LatentDirichletAllocation with evaluate_every > 0-->
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#### Steps/Code to Reproduce
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<!--
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Example:
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```python
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import openml
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openml.flows.get_flow(1)
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```
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If the code is too long, feel free to put it in a public gist and link
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it in the issue: https://gist.github.com
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-->
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#### Expected Results
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<!-- Example: No error is thrown. Please paste or describe the expected results.-->
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#### Actual Results
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<!-- Please paste or specifically describe the actual output or traceback. -->
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#### Versions
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<!--
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Please run the following snippet and paste the output below.
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import platform; print(platform.platform())
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import sys; print("Python", sys.version)
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import numpy; print("NumPy", numpy.__version__)
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import scipy; print("SciPy", scipy.__version__)
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import sklearn; print("Scikit-Learn", sklearn.__version__)
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import openml; print("OpenML", openml.__version__)
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-->
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<!-- Thanks for contributing! -->

‎LICENSE‎

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BSD 3-Clause License
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Copyright (c) 2014-2018, Matthias Feurer, Jan van Rijn, Andreas Müller,
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Joaquin Vanschoren and others.
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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* Neither the name of the copyright holder nor the names of its
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contributors may be used to endorse or promote products derived from
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this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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License of the files CONTRIBUTING.md, ISSUE_TEMPLATE.md and
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PULL_REQUEST_TEMPLATE.md:
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Those files are modifications of the respecting templates in scikit-learn and
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they are licensed under a New BSD license:
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New BSD License
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Copyright (c) 2007–2018 The scikit-learn developers.
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are met:
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a. Redistributions of source code must retain the above copyright notice,
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this list of conditions and the following disclaimer.
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b. Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in the
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documentation and/or other materials provided with the distribution.
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c. Neither the name of the Scikit-learn Developers nor the names of
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its contributors may be used to endorse or promote products
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derived from this software without specific prior written
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permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR
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ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
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OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH
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DAMAGE.

‎PULL_REQUEST_TEMPLATE.md‎

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<!--
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Thanks for contributing a pull request to the OpenML python connector! Please ensure you have taken a look at
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the contribution guidelines: https://github.com/openml/openml-python/blob/master/CONTRIBUTING.md#Contributing-Pull-Requests
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Please make sure that:
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* this pull requests is against the `develop` branch
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* you updated all docs
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-->
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#### Reference Issue
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<!-- Example: Fixes #1234 -->
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#### What does this PR implement/fix? Explain your changes.
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#### How should this PR be tested?
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#### Any other comments?
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‎appveyor.yml‎

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environment:
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global:
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CMD_IN_ENV: "cmd /E:ON /V:ON /C .\\appveyor\\scikit-learn-contrib\\run_with_env.cmd"
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matrix:
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- PYTHON: "C:\\Python35-x64"
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PYTHON_VERSION: "3.5"
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PYTHON_ARCH: "64"
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MINICONDA: "C:\\Miniconda35-x64"
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- PYTHON: "C:\\Python35"
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PYTHON_VERSION: "3.5"
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PYTHON_ARCH: "32"
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MINICONDA: "C:\\Miniconda35"
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matrix:
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fast_finish: true
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install:
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# Miniconda is pre-installed in the worker build
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- "SET PATH=%MINICONDA%;%MINICONDA%\\Scripts;%PATH%"
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- "python -m pip install -U pip"
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# Check that we have the expected version and architecture for Python
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- "python --version"
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- "python -c \"import struct; print(struct.calcsize('P') * 8)\""
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- "pip --version"
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# Remove cygwin because it clashes with conda
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# see http://help.appveyor.com/discussions/problems/3712-git-remote-https-seems-to-be-broken
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- rmdir C:\\cygwin /s /q
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# Update previous packages and install the build and runtime dependencies of the project.
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# XXX: setuptools>23 is currently broken on Win+py3 with numpy
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# (https://github.com/pypa/setuptools/issues/728)
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- conda update --all --yes setuptools=23
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# Install the build and runtime dependencies of the project.
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- "cd C:\\projects\\openml-python"
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- conda install --quiet --yes mock numpy scipy nose requests scikit-learn nbformat python-dateutil nbconvert
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- pip install liac-arff xmltodict oslo.concurrency
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- "%CMD_IN_ENV% python setup.py install"
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# Not a .NET project, we build scikit-learn in the install step instead
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build: false
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test_script:
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- "cd C:\\projects\\openml-python"
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- "%CMD_IN_ENV% python setup.py test"

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