8000 Merge pull request #22116 from melissawm/add-sphinx-design · numpy/numpy@b6a3e83 · GitHub
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Merge pull request #22116 from melissawm/add-sphinx-design
MAINT,DOC: Remove sphinx-panels in favor of sphinx-design
2 parents c2ddceb + 9de446a commit b6a3e83

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‎doc/source/_static/numpy.css

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@@ -64,25 +64,29 @@ Nat Methods 8, 441 (2011). https://doi.org/10.1038/nmeth.1618
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/* Main page overview cards */
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.intro-card {
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.sd-card {
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background: #fff;
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border-radius: 0;
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padding: 30px 10px 20px 10px;
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margin: 10px 0px;
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}
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.intro-card p.card-text {
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.sd-card .sd-card-header {
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text-align: center;
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}
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.sd-card .sd-card-header .sd-card-text {
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margin: 0px;
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}
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.intro-card .card-img-top {
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.sd-card .sd-card-img-top {
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height: 52px;
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width: 52px;
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margin-left: auto;
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margin-right: auto;
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}
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.intro-card .card-header {
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.sd-card .sd-card-header {
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border: none;
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background-color: white;
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color: #150458 !important;
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padding: 2.5rem 0rem 0.5rem 0rem;
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}
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.intro-card .card-footer {
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.sd-card .sd-card-footer {
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border: none;
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background-color: white;
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}
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.intro-card .card-footer p.card-text {
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.sd-card .sd-card-footer .sd-card-text {
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max-width: 220px;
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margin-left: auto;
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margin-right: auto;
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}
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/* Dark theme tweaking */
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html[data-theme=dark] .intro-card img[src*='.svg'] {
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html[data-theme=dark] .sd-card img[src*='.svg'] {
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filter: invert(0.82) brightness(0.8) contrast(1.2);
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}
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/* Main index page overview cards */
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html[data-theme=dark] .shadow {
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box-shadow: 0 .5rem 1rem rgba(250, 250, 250, .6) !important
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html[data-theme=dark] .sd-card {
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background-color:var(--pst-color-background);
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}
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html[data-theme=dark] .sd-shadow-sm {
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box-shadow: 0 .1rem 1rem rgba(250, 250, 250, .6) !important
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}
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html[data-theme=dark] .intro-card .card-header {
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html[data-theme=dark] .sd-card .sd-card-header {
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background-color:var(--pst-color-background);
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color: #150458 !important;
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html[data-theme=dark] .intro-card .card-footer {
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html[data-theme=dark] .sd-card .sd-card-footer {
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background-color:var(--pst-color-background);
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}
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‎doc/source/conf.py

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@@ -84,7 +84,7 @@ class PyTypeObject(ctypes.Structure):
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'IPython.sphinxext.ipython_console_highlighting',
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'IPython.sphinxext.ipython_directive',
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'sphinx.ext.mathjax',
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'sphinx_panels',
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'sphinx_design',
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]
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skippable_extensions = [
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html_last_updated_fmt = '%b %d, %Y'
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html_css_files = ["numpy.css"]
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html_context = {"default_mode": "light"}
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# Prevent sphinx-panels from loading bootstrap css, the pydata-sphinx-theme
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# already loads it
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panels_add_bootstrap_css = False
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html_use_modindex = True
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html_copy_source = False
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html_domain_indices = False

‎doc/source/index.rst

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@@ -34,76 +34,84 @@ fast operations on arrays, including mathematical, logical, shape manipulation,
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sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra,
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basic statistical operations, random simulation and much more.
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.. panels::
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:card: + intro-card text-center
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:column: col-lg-6 col-md-6 col-sm-6 col-xs-12 d-flex
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---
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:img-top: ../source/_static/index-images/getting_started.svg
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Getting Started
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^^^^^^^^^^^^^^^
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.. grid:: 2
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New to NumPy? Check out the Absolute Beginner's Guide. It contains an
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introduction to NumPy's main concepts and links to additional tutorials.
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.. grid-item-card::
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:img-top: ../source/_static/index-images/getting_started.svg
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Getting Started
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^^^^^^^^^^^^^^^
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.. link-button:: user/absolute_beginners
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:type: ref
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:text: To the absolute beginner's guide
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:classes: btn-block btn-secondary stretched-link
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---
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:img-top: ../source/_static/index-images/user_guide.svg
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New to NumPy? Check out the Absolute Beginner's Guide. It contains an
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introduction to NumPy's main concepts and links to additional tutorials.
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User Guide
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^^^^^^^^^^
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The user guide provides in-depth information on the
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key concepts of NumPy with useful background information and explanation.
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.. button-ref:: user/absolute_beginners
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:expand:
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:color: secondary
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:click-parent:
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To the absolute beginner's guide
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.. link-button:: user
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:type: ref
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:text: To the user guide
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:classes: btn-block btn-secondary stretched-link
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.. grid-item-card::
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:img-top: ../source/_static/index-images/user_guide.svg
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---
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:img-top: ../source/_static/index-images/api.svg
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User Guide
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^^^^^^^^^^
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API Reference
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^^^^^^^^^^^^^
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The user guide provides in-depth information on the
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key concepts of NumPy with useful background information and explanation.
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The reference guide contains a detailed description of the functions,
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modules, and objects included in NumPy. The reference describes how the
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methods work and which parameters can be used. It assumes that you have an
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understanding of the key concepts.
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.. button-ref:: user
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:expand:
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:color: secondary
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:click-parent:
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.. link-button:: reference
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:type: ref
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:text: To the reference guide
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:classes: btn-block btn-secondary stretched-link
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To the user guide
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---
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:img-top: ../source/_static/index-images/contributor.svg
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.. grid-item-card::
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:img-top: ../source/_static/index-images/api.svg
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Contributor's Guide
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^^^^^^^^^^^^^^^^^^^
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API Reference
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^^^^^^^^^^^^^
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Want to add to the codebase? Can help add translation or a flowchart to the
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documentation? The contributing guidelines will guide you through the
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process of improving NumPy.
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The reference guide contains a detailed description of the functions,
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modules, and objects included in NumPy. The reference describes how the
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methods work and which parameters can be used. It assumes that you have an
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understanding of the key concepts.
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.. link-button:: devindex
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:type: ref
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:text: To the contributor's guide
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:classes: btn-block btn-secondary stretched-link
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.. button-ref:: reference
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:expand:
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:color: secondary
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:click-parent:
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To the reference guide
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.. grid-item-card::
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:img-top: ../source/_static/index-images/contributor.svg
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Contributor's Guide
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^^^^^^^^^^^^^^^^^^^
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Want to add to the codebase? Can help add translation or a flowchart to the
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documentation? The contributing guidelines will guide you through the
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process of improving NumPy.
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.. button-ref:: devindex
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:expand:
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:color: secondary
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:click-parent:
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To the contributor's guide
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.. This is not really the index page, that is found in
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_templates/indexcontent.html The toctree content here will be added to the

‎doc/source/reference/arrays.interface.rst

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**data** (optional)
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A 2-tuple whose first argument is a :doc:`Python integer <c-api/long>`
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A 2-tuple whose first argument is a :doc:`Python integer <python:c-api/long>`
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that points to the data-area storing the array contents.
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.. note::
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:obj:`__array_struct__` is considered legacy and should not be used for new
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code. Use the :py:doc:`buffer protocol <c-api/buffer>` or the DLPack protocol
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code. Use the :doc:`buffer protocol <python:c-api/buffer>` or the DLPack protocol
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`numpy.from_dlpack` instead.
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‎doc/source/user/basics.interoperability.rst

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encounter a foreign object, they will try (in order):
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1. The buffer protocol, described :py:doc:`in the Python C-API documentation
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<c-api/buffer>`.
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<python:c-api/buffer>`.
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2. The ``__array_interface__`` protocol, described
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:ref:`in this page <arrays.interface>`. A precursor to Python's buffer
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protocol, it defines a way to access the contents of a NumPy array from other

‎doc/source/user/how-to-how-to.rst

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and `References`, which give complete, authoritative data on some concrete
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part of NumPy (like its API) but aren't obligated to paint a broader picture.
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For more on tutorials, see :doc:`content/tutorial-style-guide`
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For more on tutorials, see :doc:`numpy-tutorials:content/tutorial-style-guide`
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******************************************************************************
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Is this page an example of a how-to?

‎doc/source/user/quickstart.rst

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- `SciPy Tutorial <https://docs.scipy.org/doc/scipy/ref 10000 erence/tutorial/index.html>`__
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- `SciPy Lecture Notes <https://scipy-lectures.org>`__
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- A `matlab, R, IDL, NumPy/SciPy dictionary <http://mathesaurus.sf.net/>`__
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- :doc:`tutorial-svd <content/tutorial-svd>`
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- :doc:`tutorial-svd <numpy-tutorials:content/tutorial-svd>`

‎doc_requirements.txt

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sphinx>=4.5.0
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numpydoc==1.4
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pydata-sphinx-theme==0.9.0
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sphinx-design
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ipython!=8.1.0
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scipy
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matplotlib

‎environment.yml

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- typing_extensions>=4.2.0
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- sphinx>=4.5.0
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- sphinx-panels
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- sphinx-design
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- numpydoc=1.4.0
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- ipython
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‎numpy/core/_add_newdocs.py

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In such cases, the use of `numpy.linspace` should be preferred.
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The built-in :py:class:`range` generates :std:doc:`Python built-in integers
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that have arbitrary size <c-api/long>`, while `numpy.arange` produces
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`numpy.int32` or `numpy.int64` numbers. This may result in incorrect
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results for large integer values::
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that have arbitrary size <python:c-api/long>`, while `numpy.arange`
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produces `numpy.int32` or `numpy.int64` numbers. This may result in
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incorrect results for large integer values::
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>>> power = 40
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>>> modulo = 10000

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