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Add sphinx templates from 412-user-guide-and-api-documentation
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div.docutils.container.index-features { | ||
width: 450px; | ||
} | ||
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div.docutils.container.index-box { | ||
background-color: var(--pst-color-white-highlight); | ||
border-radius: 10px; | ||
color: black; | ||
padding: 5px; | ||
margin-left: 15px; | ||
float: right; | ||
width: 400px; | ||
} | ||
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/* Need to be able to have absolute positioning for the div inside */ | ||
.bd-main .bd-content .bd-article-container .bd-article { | ||
position: relative; | ||
} | ||
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@media (min-width: 792px) { | ||
div.docutils.container.index-features { | ||
position: absolute; | ||
top: 10px; | ||
right: 0px; | ||
} | ||
} | ||
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@media (min-width: 1092px) { | ||
div.docutils.container.index-box { | ||
margin-left: 30px; | ||
margin-right: -15px; | ||
} | ||
} | ||
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@media (max-width: 892px) { | ||
div.docutils.container.index-box { | ||
max-width: 500px; | ||
width: unset; | ||
float: unset; | ||
margin-left: auto; | ||
margin-right: auto; | ||
} | ||
} |
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:mod:`{{module}}`.{{objname}} | ||
{{ underline }}============== | ||
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.. rst-class:: side_comment | ||
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Usage examples at the bottom of this page. | ||
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.. currentmodule:: {{ module }} | ||
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.. autoclass:: {{ objname }} | ||
:inherited-members: | ||
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{% block methods %} | ||
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{% endblock %} | ||
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.. raw:: html | ||
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<div class="clearer"></div> |
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:mod:`{{module}}`.{{objname}} | ||
{{ underline }}==================== | ||
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.. currentmodule:: {{ module }} | ||
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.. autofunction:: {{ objname }} | ||
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.. raw:: html | ||
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<div class="clearer"></div> |
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API | ||
=== | ||
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.. currentmodule:: skore | ||
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This page lists all the public functions and classes of the ``skore`` | ||
package. | ||
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The ``skore`` UI | ||
---------------- | ||
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These classes are meant for ``skore``'s user interface. | ||
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.. autosummary:: | ||
:toctree: generated/ | ||
:template: class.rst | ||
:nosignatures: | ||
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Project | ||
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.. autosummary:: | ||
:toctree: generated/ | ||
:template: function.rst | ||
:nosignatures: | ||
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load | ||
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The ``skore`` machine learning programming assistant | ||
---------------------------------------------------- | ||
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These functions and classes enhance ``scikit-learn``'s ones. | ||
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.. autosummary:: | ||
:toctree: generated/ | ||
:template: function.rst | ||
:nosignatures: | ||
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cross_validate |
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.. _getting_started: | ||
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Getting started | ||
=============== | ||
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``skore`` UI | ||
------------ | ||
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.. currentmodule:: skore | ||
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From your shell, initialize a skore project, here named ``project.skore``, that | ||
will be in your current working directory: | ||
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.. code:: console | ||
python -m skore create "project.skore" | ||
Then, from your Python code (in the same directory), load the project and store | ||
an integer for example: | ||
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.. code-block:: python | ||
from skore import load | ||
project = load("project.skore") | ||
project.put("my_int", 3) | ||
Finally, from your shell (in the same directory), start the UI locally: | ||
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.. code:: console | ||
python -m skore launch project.skore | ||
This will automatically open a browser at the UI's location: | ||
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#. On the top left, create a new ``View``. | ||
#. From the ``Elements`` section on the bottom left, you can add stored items to this view, either by double-cliking on them or by doing drag-and-drop. | ||
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For more features, please look into :ref:`auto_examples`. | ||
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.. image:: https://raw.githubusercontent.com/sylvaincom/sylvaincom.github.io/master/files/probabl/skore/2024_10_14_skore_demo.gif | ||
:alt: Getting started with ``skore`` demo |
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.. You can adapt this file completely to your liking, but it should at least | ||
contain the root `toctree` directive. | ||
Welcome to ``skore`` | ||
==================== | ||
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With skore, data scientists can: | ||
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#. Track and visualize their ML/DS results. | ||
#. Get assistance when developing their ML/DS projects. | ||
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- Scikit-learn compatible :func:`~skore.cross_validate` provides insights and checks on cross-validation. | ||
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These are only the initial features: skore is a work in progress and aims to be | ||
an end-to-end library for data scientists. | ||
Stay tuned! | ||
Feedbacks are welcome: please feel free to join our `Discord <http://discord.probabl.ai>`_ or `create an issue <https://github.com/probabl-ai/skore/issues>`_. | ||
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We are a product team working at `Probabl <https://probabl.ai>`_ and our motto is #OwnYourDataScience. | ||
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- License: BSD | ||
- GitHub repository: https://github.com/probabl-ai/skore | ||
- Discord: http://discord.probabl.ai | ||
- Status: under development, API is subject to change. | ||
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.. image:: https://raw.githubusercontent.com/sylvaincom/sylvaincom.github.io/master/files/probabl/skore/2024_10_14_skore_demo.gif | ||
:alt: Getting started with skore demo | ||
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.. currentmodule:: skore | ||
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.. toctree:: | ||
:maxdepth: 2 | ||
:caption: Contents: | ||
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install | ||
getting_started | ||
auto_examples/index | ||
user_guide | ||
api |
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.. _install: | ||
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Install | ||
======= | ||
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.. currentmodule:: skore | ||
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First of all, we recommend using a `virtual environment (venv) <https://docs.python.org/3/tutorial/venv.html>`_. | ||
You need ``python>=3.9``. | ||
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Then, you can install ``skore`` by using ``pip``: | ||
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.. code:: console | ||
pip install -U skore | ||
You can check ``skore``'s latest version on `PyPI <https://pypi.org/project/skore/>`_. | ||
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🚨 For Windows users, the encoding must be set to | ||
`UTF-8 <https://docs.python.org/3/using/windows.html#utf-8-mode>`_: | ||
see `PYTHONUTF8 <https://docs.python.org/3/using/cmdline.html#envvar-PYTHONUTF8>`_. |
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.. _user_guide: | ||
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User guide | ||
========== | ||
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.. currentmodule:: skore | ||
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*The User Guide is currently work in progress and will be released soon, thank | ||
you for your patience!* | ||
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For now, please look into: | ||
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.. toctree:: | ||
:maxdepth: 2 | ||
:caption: Contents: | ||
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install | ||
getting_started | ||
auto_examples/index | ||
api |
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.. _getting_started: | ||
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Getting started with ``skore`` | ||
============================== | ||
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This example builds on top of the :ref:`getting_started` guide. | ||
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``skore`` UI | ||
------------ | ||
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This section provides a quick start to the ``skore`` UI, an open-source package that aims to enable data scientists to: | ||
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#. Store objects of different types from their Python code: python lists, ``scikit-learn`` fitted pipelines, ``plotly`` figures, and more. | ||
#. Track and visualize these stored objects on a user-friendly dashboard. | ||
#. Export the dashboard to a HTML file. | ||
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Initialize a Project and launch the UI | ||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | ||
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From your shell, initialize a skore project, here named ``project``, that will be | ||
in your current working directory: | ||
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.. code:: console | ||
python -m skore create "project" | ||
This will create a ``skore`` project directory named ``project`` in the current | ||
directory. | ||
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From your shell (in the same directory), start the UI locally: | ||
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.. code:: console | ||
python -m skore launch "project" | ||
This will automatically open a browser at the UI's location. | ||
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Now that the project file exists, we can load it in our notebook so that we can | ||
read from and write to it: | ||
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.. code-block:: python | ||
from skore import load | ||
project = load("project.skore") | ||
Storing some items | ||
------------------ | ||
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Storing an integer: | ||
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.. code-block:: python | ||
project.put("my_int", 3) | ||
Here, the name of my stored item is ``my_int`` and the integer value is 3. | ||
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For a ``pandas`` data frame: | ||
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.. code-block:: python | ||
import numpy as np | ||
import pandas as pd | ||
my_df = pd.DataFrame(np.random.randn(3, 3)) | ||
project.put("my_df", my_df) | ||
For a ``matplotlib`` figure: | ||
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.. code-block:: python | ||
import matplotlib.pyplot as plt | ||
x = [0, 1, 2, 3, 4, 5] | ||
fig, ax = plt.subplots(figsize=(5, 3), layout="constrained") | ||
_ = ax.plot(x) | ||
project.put("my_figure", fig) | ||
For a ``scikit-learn`` fitted pipeline: | ||
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.. code-block:: python | ||
from sklearn.datasets import load_diabetes | ||
from sklearn.linear_model import Lasso | ||
from sklearn.pipeline import Pipeline | ||
from sklearn.preprocessing import StandardScaler | ||
diabetes = load_diabetes() | ||
X = diabetes.data[:150] | ||
y = diabetes.target[:150] | ||
my_pipeline = Pipeline( | ||
[("standard_scaler", StandardScaler()), ("lasso", Lasso(alpha=2))] | ||
) | ||
my_pipeline.fit(X, y) | ||
project.put("my_fitted_pipeline", my_pipeline) | ||
Back to the dashboard | ||
^^^^^^^^^^^^^^^^^^^^^ | ||
#. On the top left, create a new ``View``. | ||
#. From the ``Elements`` section on the bottom left, you can add stored items to this view, either by double-cliking on them or by doing drag-and-drop. | ||
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.. image:: https://raw.githubusercontent.com/sylvaincom/sylvaincom.github.io/master/files/probabl/skore/2024_10_14_skore_demo.gif | ||
:alt: Getting started with ``skore`` demo |