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fixed few broken links and cleaned up grammar
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docs/details.md

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## Configuration
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The configuration file resides in a directory `.config/openml` in the
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The configuration file resides in a directory `~/.config/openml` in the
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home directory of the user and is called config (More specifically, it
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resides in the [configuration directory specified by the XDGB Base
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resides in the [configuration directory specified by the XDG Base
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Directory
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Specification](https://specifications.freedesktop.org/basedir-spec/basedir-spec-latest.html)).
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It consists of `key = value` pairs which are separated by newlines. The
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following keys are defined:
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- apikey: required to access the server.
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- server: the server to connect to (default: `http://www.openml.org`).
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For connection to the test server, set this to `test.openml.org`.
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- server: the server to connect to (default: `https://www.openml.org`).
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For connection to the test server, set this to `https://test.openml.org`.
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- cachedir: the root folder where the cache file directories should be created.
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If not given, will default to `~/.openml/cache`
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- avoid_duplicate_runs: if set to `True` (default), when certain functions

docs/extensions.md

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flows and runs from a specific library, an additional interface can be
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built. The OpenML-Python team does not have the capacity to develop and
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maintain such interfaces on its own. For this reason, we have built an
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extension interface to allows others to contribute back. Building a
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suitable extension for therefore requires an understanding of the
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extension interface to allow others to contribute back. Building a
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suitable extension therefore requires an understanding of the
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current OpenML-Python support.
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[This tutorial](../examples/Basics/simple_flows_and_runs_tutorial) shows how the scikit-learn
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Typically, the flow-dependency field is used to check whether
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the specific library is present, and no unknown libraries are
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present there.
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- `can_handle_model`: Similar as
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`can_handle_flow`:, except that in
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- `can_handle_model`: Similar to
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`can_handle_flow`, except that in
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this case a Python object is given. As such, in many cases, this
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method can be implemented by checking whether this adheres to a
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certain base class.
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with the [OpenML-Python repository](https://github.com/openml/openml-python).
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The extension repository should work off-the-shelf with *OpenML-Python* installed.
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Create a public Github repo with the following directory structure:
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Create a public GitHub repo with the following directory structure:
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| [repo name]
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| |-- [extension name]
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### Recommended
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- Test cases to keep the extension up to date with the
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Openml-Python upstream changes.
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OpenML-Python upstream changes.
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- Documentation of the extension API, especially if any new
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functionality added to OpenML-Python\'s extension design.
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- Examples to show how the new extension interfaces and works with

docs/index.md

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Feurer, Matthias, et al.
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"OpenML-Python: an extensible Python API for OpenML."
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_Journal of Machine Learning Research_ 22.100 (2021):1−5.
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_Journal of Machine Learning Research_ 22.100 (2021): 1−5.

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