http:// → https:// (#9748)

Author: DimitriPapadopoulos

.github/ISSUE_TEMPLATE/bugreport.yml

@@ -37,7 +37,7 @@ body:
         Please confirm that the bug report is in an excellent state, so we can understand & fix it quickly & efficiently. For more details, check out:
 
         - [Minimal Complete Verifiable Examples](https://stackoverflow.com/help/mcve)
-        - [Craft Minimal Bug Reports](http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports)
+        - [Craft Minimal Bug Reports](https://matthewrocklin.com/minimal-bug-reports)
 
       options:
         - label: Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.

.github/config.yml

@@ -14,7 +14,7 @@ newIssueWelcomeComment: >
 newPRWelcomeComment: >
   Thank you for opening this pull request! It may take us a few days to respond here, so thank you for being patient.
 
-  If you have questions, some answers may be found in our [contributing guidelines](http://docs.xarray.dev/en/stable/contributing.html).
+  If you have questions, some answers may be found in our [contributing guidelines](https://docs.xarray.dev/en/stable/contributing.html).
 
 # Comment to be posted to on pull requests merged by a first time user
 firstPRMergeComment: >

CODE_OF_CONDUCT.md

@@ -40,7 +40,7 @@ Project maintainers who do not follow or enforce the Code of Conduct in good fai
 
 ## Attribution
 
-This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4, available at [http://contributor-covenant.org/version/1/4][version]
+This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4, available at [https://contributor-covenant.org/version/1/4][version]
 
-[homepage]: http://contributor-covenant.org
-[version]: http://contributor-covenant.org/version/1/4/
+[homepage]: https://contributor-covenant.org
+[version]: https://contributor-covenant.org/version/1/4/

CONTRIBUTING.md

@@ -1 +1 @@
-Xarray's contributor guidelines [can be found in our online documentation](http://docs.xarray.dev/en/stable/contributing.html)
+Xarray's contributor guidelines [can be found in our online documentation](https://docs.xarray.dev/en/stable/contributing.html)

README.md

@@ -94,7 +94,7 @@ our efforts.
 ## History
 
 Xarray is an evolution of an internal tool developed at [The Climate
-Corporation](http://climate.com/). It was originally written by Climate
+Corporation](https://climate.com/). It was originally written by Climate
 Corp researchers Stephan Hoyer, Alex Kleeman and Eugene Brevdo and was
 released as open source in May 2014. The project was renamed from
 "xray" in January 2016. Xarray became a fiscally sponsored project of

asv_bench/asv.conf.json

@@ -7,7 +7,7 @@
     "project": "xarray",
 
     // The project's homepage
-    "project_url": "http://docs.xarray.dev/",
+    "project_url": "https://docs.xarray.dev/",
 
     // The URL or local path of the source code repository for the
     // project being benchmarked

design_notes/flexible_indexes_notes.md

@@ -133,7 +133,7 @@ A possible, more explicit solution to reuse a `pandas.MultiIndex` in a DataArray
 
 New indexes may also be built from existing sets of coordinates or variables in a Dataset/DataArray using the `.set_index()` method.
 
-The [current signature](http://docs.xarray.dev/en/stable/generated/xarray.DataArray.set_index.html#xarray.DataArray.set_index) of `.set_index()` is tailored to `pandas.MultiIndex` and tied to the concept of a dimension-index. It is therefore hardly reusable as-is in the context of flexible indexes proposed here.
+The [current signature](https://docs.xarray.dev/en/stable/generated/xarray.DataArray.set_index.html#xarray.DataArray.set_index) of `.set_index()` is tailored to `pandas.MultiIndex` and tied to the concept of a dimension-index. It is therefore hardly reusable as-is in the context of flexible indexes proposed here.
 
 The new signature may look like one of these:
 

doc/contributing.rst

@@ -7,7 +7,7 @@ Contributing to xarray
 .. note::
 
   Large parts of this document came from the `Pandas Contributing
-  Guide <http://pandas.pydata.org/pandas-docs/stable/contributing.html>`_.
+  Guide <https://pandas.pydata.org/pandas-docs/stable/development/contributing.html>`_.
 
 Overview
 ========
@@ -68,7 +68,7 @@ If you are reporting a bug, please use the provided template which includes the
 
 #. Include a short, self-contained Python snippet reproducing the problem.
    You can format the code nicely by using `GitHub Flavored Markdown
-   <http://github.github.com/github-flavored-markdown/>`_::
+   <https://github.github.com/github-flavored-markdown/>`_::
 
       ```python
       import xarray as xr
@@ -106,7 +106,7 @@ Version control, Git, and GitHub
 
 The code is hosted on `GitHub <https://www.github.com/pydata/xarray>`_. To
 contribute you will need to sign up for a `free GitHub account
-<https://github.com/signup/free>`_. We use `Git <http://git-scm.com/>`_ for
+<https://github.com/signup/free>`_. We use `Git <https://git-scm.com/>`_ for
 version control to allow many people to work together on the project.
 
 Some great resources for learning Git:
@@ -327,7 +327,7 @@ To return to your root environment::
 
       conda deactivate
 
-See the full `conda docs here <http://conda.pydata.org/docs>`__.
+See the full `conda docs here <https://conda.pydata.org/docs>`__.
 
 Install pre-commit hooks
 ------------------------
@@ -365,9 +365,9 @@ About the *xarray* documentation
 --------------------------------
 
 The documentation is written in **reStructuredText**, which is almost like writing
-in plain English, and built using `Sphinx <http://sphinx-doc.org/>`__. The
+in plain English, and built using `Sphinx <https://www.sphinx-doc.org/>`__. The
 Sphinx Documentation has an excellent `introduction to reST
-<http://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html>`__. Review the Sphinx docs to perform more
+<https://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html>`__. Review the Sphinx docs to perform more
 complex changes to the documentation as well.
 
 Some other important things to know about the docs:
@@ -388,7 +388,7 @@ Some other important things to know about the docs:
   extend it in a similar manner.
 
 - The tutorials make heavy use of the `ipython directive
-  <http://matplotlib.org/sampledoc/ipython_directive.html>`_ sphinx extension.
+  <https://matplotlib.org/sampledoc/ipython_directive.html>`_ sphinx extension.
   This directive lets you put code in the documentation which will be run
   during the doc build. For example:
 
@@ -551,7 +551,7 @@ xarray uses several tools to ensure a consistent code format throughout the proj
 
 - `ruff <https://github.com/astral-sh/ruff>`_ for formatting, code quality checks and standardized order in imports
 - `absolufy-imports <https://github.com/MarcoGorelli/absolufy-imports>`_ for absolute instead of relative imports from different files,
-- `mypy <http://mypy-lang.org/>`_ for static type checking on `type hints
+- `mypy <https://mypy-lang.org/>`_ for static type checking on `type hints
   <https://docs.python.org/3/library/typing.html>`_.
 
 We highly recommend that you setup `pre-commit hooks <https://pre-commit.com/>`_
@@ -624,7 +624,7 @@ Test-driven development/code writing
 ------------------------------------
 
 *xarray* is serious about testing and strongly encourages contributors to embrace
-`test-driven development (TDD) <http://en.wikipedia.org/wiki/Test-driven_development>`_.
+`test-driven development (TDD) <https://en.wikipedia.org/wiki/Test-driven_development>`_.
 This development process "relies on the repetition of a very short development cycle:
 first the developer writes an (initially failing) automated test case that defines a desired
 improvement or new function, then produces the minimum amount of code to pass that test."
@@ -636,7 +636,7 @@ Adding tests is one of the most common requests after code is pushed to *xarray*
 it is worth getting in the habit of writing tests ahead of time so that this is never an issue.
 
 Like many packages, *xarray* uses `pytest
-<http://doc.pytest.org/en/latest/>`_ and the convenient
+<https://doc.pytest.org/en/latest/>`_ and the convenient
 extensions in `numpy.testing
 <https://numpy.org/doc/stable/reference/routines.testing.html>`_.
 
@@ -669,7 +669,7 @@ typically find tests wrapped in a class.
     class TestReallyCoolFeature: ...
 
 Going forward, we are moving to a more *functional* style using the
-`pytest <http://doc.pytest.org/en/latest/>`__ framework, which offers a richer
+`pytest <https://doc.pytest.org/en/latest/>`__ framework, which offers a richer
 testing framework that will facilitate testing and developing. Thus, instead of
 writing test classes, we will write test functions like this:
 
@@ -816,7 +816,7 @@ speed up local testing on multicore machines, by running pytest with the optiona
 This can significantly reduce the time it takes to locally run tests before
 submitting a pull request.
 
-For more, see the `pytest <http://doc.pytest.org/en/latest/>`_ documentation.
+For more, see the `pytest <https://doc.pytest.org/en/latest/>`_ documentation.
 
 Running the performance test suite
 ----------------------------------
@@ -891,7 +891,7 @@ Learn `how to write a benchmark and how to use asv from the documentation <https
          see https://github.com/pydata/xarray/pull/5066
 
    The *xarray* benchmarking suite is run remotely and the results are
-   available `here <http://pandas.pydata.org/speed/xarray/>`_.
+   available `here <https://pandas.pydata.org/speed/xarray/>`_.
 
 Documenting your code
 ---------------------
@@ -1062,7 +1062,7 @@ PR checklist
 - **Test your code**.
 
   - Write new tests if needed. See `"Test-driven development/code writing" <https://docs.xarray.dev/en/stable/contributing.html#test-driven-development-code-writing>`_.
-  - Test the code using `Pytest <http://doc.pytest.org/en/latest/>`_. Running all tests (type ``pytest`` in the root directory) takes a while, so feel free to only run the tests you think are needed based on your PR (example: ``pytest xarray/tests/test_dataarray.py``). CI will catch any failing tests.
+  - Test the code using `Pytest <https://doc.pytest.org/en/latest/>`_. Running all tests (type ``pytest`` in the root directory) takes a while, so feel free to only run the tests you think are needed based on your PR (example: ``pytest xarray/tests/test_dataarray.py``). CI will catch any failing tests.
   - By default, the upstream dev CI is disabled on pull request and push events. You can override this behavior per commit by adding a ``[test-upstream]`` tag to the first line of the commit message. For documentation-only commits, you can skip the CI per commit by adding a ``[skip-ci]`` tag to the first line of the commit message.
 
 - **Properly format your code** and verify that it passes the formatting guidelines set by `ruff <https://github.com/astral-sh/ruff>`_. See `"Code formatting" <https://docs.xarray.dev/en/stablcontributing.html#code-formatting>`_. You can use `pre-commit <https://pre-commit.com/>`_ to run these automatically on each commit.

doc/ecosystem.rst

@@ -52,7 +52,7 @@ Geosciences
 - `xclim <https://xclim.readthedocs.io/>`_: A library for calculating climate science indices with unit handling built from xarray and dask.
 - `xESMF <https://pangeo-xesmf.readthedocs.io/>`_: Universal regridder for geospatial data.
 - `xgcm <https://xgcm.readthedocs.io/>`_: Extends the xarray data model to understand finite volume grid cells (common in General Circulation Models) and provides interpolation and difference operations for such grids.
-- `xmitgcm <http://xmitgcm.readthedocs.io/>`_: a python package for reading `MITgcm <https://mitgcm.org/>`_ binary MDS files into xarray data structures.
+- `xmitgcm <https://xmitgcm.readthedocs.io/>`_: a python package for reading `MITgcm <https://mitgcm.org/>`_ binary MDS files into xarray data structures.
 - `xnemogcm <https://github.com/rcaneill/xnemogcm/>`_: a package to read `NEMO <https://nemo-ocean.eu/>`_ output files and add attributes to interface with xgcm.
 
 Machine Learning
@@ -87,11 +87,11 @@ Extend xarray capabilities
 - `xr-scipy <https://xr-scipy.readthedocs.io>`_: A lightweight scipy wrapper for xarray.
 - `X-regression <https://github.com/kuchaale/X-regression>`_: Multiple linear regression from Statsmodels library coupled with Xarray library.
 - `xskillscore <https://github.com/xarray-contrib/xskillscore>`_: Metrics for verifying forecasts.
-- `xyzpy <http://xyzpy.readthedocs.io>`_: Easily generate high dimensional data, including parallelization.
+- `xyzpy <https://xyzpy.readthedocs.io>`_: Easily generate high dimensional data, including parallelization.
 
 Visualization
 ~~~~~~~~~~~~~
-- `datashader <https://datashader.org>`_, `geoviews <http://geoviews.org>`_, `holoviews <http://holoviews.org/>`_, : visualization packages for large data.
+- `datashader <https://datashader.org>`_, `geoviews <https://geoviews.org>`_, `holoviews <https://holoviews.org/>`_, : visualization packages for large data.
 - `hvplot <https://hvplot.pyviz.org/>`_ : A high-level plotting API for the PyData ecosystem built on HoloViews.
 - `psyplot <https://psyplot.readthedocs.io>`_: Interactive data visualization with python.
 - `xarray-leaflet <https://github.com/davidbrochart/xarray_leaflet>`_: An xarray extension for tiled map plotting based on ipyleaflet.

doc/examples/ROMS_ocean_model.ipynb

@@ -11,7 +11,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The Regional Ocean Modeling System ([ROMS](http://myroms.org)) is an open source hydrodynamic model that is used for simulating currents and water properties in coastal and estuarine regions. ROMS is one of a few standard ocean models, and it has an active user community.\n",
+    "The Regional Ocean Modeling System ([ROMS](https://www.myroms.org/)) is an open source hydrodynamic model that is used for simulating currents and water properties in coastal and estuarine regions. ROMS is one of a few standard ocean models, and it has an active user community.\n",
     "\n",
     "ROMS uses a regular C-Grid in the horizontal, similar to other structured grid ocean and atmospheric models, and a stretched vertical coordinate (see [the ROMS documentation](https://www.myroms.org/wiki/Vertical_S-coordinate) for more details). Both of these require special treatment when using `xarray` to analyze ROMS ocean model output. This example notebook shows how to create a lazily evaluated vertical coordinate, and make some basic plots. The `xgcm` package is required to do analysis that is aware of the horizontal C-Grid."
    ]

doc/examples/multidimensional-coords.ipynb

@@ -126,7 +126,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In order to visualize the data on a conventional latitude-longitude grid, we can take advantage of xarray's ability to apply [cartopy](http://scitools.org.uk/cartopy/index.html) map projections."
+    "In order to visualize the data on a conventional latitude-longitude grid, we can take advantage of xarray's ability to apply [cartopy](https://scitools.org.uk/cartopy/docs/latest/) map projections."
    ]
   },
   {

doc/getting-started-guide/why-xarray.rst

@@ -106,10 +106,10 @@ under active development.
 See our technical :ref:`roadmap` for more details, and feel free to reach out
 with questions about whether xarray is the right tool for your needs.
 
-.. _datarray: https://github.com/fperez/datarray
-.. _Dask: http://dask.org
-.. _matplotlib: http://matplotlib.org
-.. _netCDF: http://www.unidata.ucar.edu/software/netcdf
-.. _NumPy: http://www.numpy.org
-.. _pandas: http://pandas.pydata.org
-.. _SciPy: http://www.scipy.org
+.. _datarray: https://github.com/BIDS/datarray
+.. _Dask: https://www.dask.org
+.. _matplotlib: https://matplotlib.org
+.. _netCDF: https://www.unidata.ucar.edu/software/netcdf
+.. _NumPy: https://numpy.org
+.. _pandas: https://pandas.pydata.org
+.. _SciPy: https://www.scipy.org

doc/roadmap.rst

@@ -148,7 +148,7 @@ implementations, e.g.:
 -  Other ndarray objects, e.g., sparse, xnd, xtensor.
 
 Our strategy has been to pursue upstream improvements in NumPy (see
-`NEP-22 <http://www.numpy.org/neps/nep-0022-ndarray-duck-typing-overview.html>`__)
+`NEP-22 <https://numpy.org/neps/nep-0022-ndarray-duck-typing-overview.html>`__)
 for supporting a complete duck-typing interface using with NumPy's
 higher level array API. Improvements in NumPy's support for custom data
 types would also be highly useful for xarray users.

doc/user-guide/dask.rst

@@ -13,7 +13,7 @@ dependency in a future version of xarray.
 
 For a full example of how to use xarray's Dask integration, read the
 `blog post introducing xarray and Dask`_. More up-to-date examples
-may be found at the `Pangeo project's gallery <http://gallery.pangeo.io/>`_
+may be found at the `Pangeo project's gallery <https://gallery.pangeo.io/>`_
 and at the `Dask examples website <https://examples.dask.org/xarray.html>`_.
 
 .. _blog post introducing xarray and Dask: https://stephanhoyer.com/2015/06/11/xray-dask-out-of-core-labeled-arrays/

doc/user-guide/io.rst

@@ -275,7 +275,7 @@ to automatically decode the values in the netCDF objects according to
 has an invalid "units" or "calendar" attribute. For these cases, you can
 turn this decoding off manually.
 
-.. _CF conventions: http://cfconventions.org/
+.. _CF conventions: https://cfconventions.org/
 
 You can view this encoding information (among others) in the
 :py:attr:`DataArray.encoding` and
@@ -343,8 +343,8 @@ See its docstring for more details.
     (``compat='override'``).
 
 
-.. _dask: http://dask.org
-.. _blog post: http://stephanhoyer.com/2015/06/11/xray-dask-out-of-core-labeled-arrays/
+.. _dask: https://www.dask.org
+.. _blog post: https://stephanhoyer.com/2015/06/11/xray-dask-out-of-core-labeled-arrays/
 
 Sometimes multi-file datasets are not conveniently organized for easy use of :py:func:`open_mfdataset`.
 One can use the ``preprocess`` argument to provide a function that takes a dataset
@@ -496,7 +496,7 @@ If character arrays are used:
   Technically, you can use
   `any string encoding recognized by Python <https://docs.python.org/3/library/codecs.html#standard-encodings>`_ if you feel the need to deviate from UTF-8,
   by setting the ``_Encoding`` field in ``encoding``. But
-  `we don't recommend it <http://utf8everywhere.org/>`_.
+  `we don't recommend it <https://utf8everywhere.org/>`_.
 - The character dimension name can be specified by the ``char_dim_name`` field of a variable's
   ``encoding``. If the name of the character dimension is not specified, the default is
   ``f'string{data.shape[-1]}'``. When decoding character arrays from existing files, the
@@ -1395,7 +1395,7 @@ For CSV files, one might also consider `xarray_extras`_.
 
 .. _xarray_extras: https://xarray-extras.readthedocs.io/en/latest/api/csv.html
 
-.. _IO tools: http://pandas.pydata.org/pandas-docs/stable/io.html
+.. _IO tools: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html
 
 
 Third party libraries

xarray/backends/zarr.py

@@ -250,9 +250,9 @@ def _determine_zarr_chunks(
     # if there are no chunks in encoding but there are dask chunks, we try to
     # use the same chunks in zarr
     # However, zarr chunks needs to be uniform for each array
-    # http://zarr.readthedocs.io/en/latest/spec/v1.html#chunks
+    # https://zarr-specs.readthedocs.io/en/latest/v2/v2.0.html#chunks
     # while dask chunks can be variable sized
-    # http://dask.pydata.org/en/latest/array-design.html#chunks
+    # https://dask.pydata.org/en/latest/array-design.html#chunks
     if var_chunks and not enc_chunks:
         if any(len(set(chunks[:-1])) > 1 for chunks in var_chunks):
             raise ValueError(
@@ -1377,7 +1377,7 @@ def open_zarr(
 
     References
     ----------
-    http://zarr.readthedocs.io/
+    https://zarr.readthedocs.io/
     """
     from xarray.backends.api import open_dataset
 

xarray/coding/strings.py

@@ -210,7 +210,7 @@ def _numpy_char_to_bytes(arr):
     # see https://github.com/numpy/numpy/issues/25916
     # and https://github.com/numpy/numpy/pull/25922
     copy = None if HAS_NUMPY_2_0 else False
-    # based on: http://stackoverflow.com/a/10984878/809705
+    # based on: https://stackoverflow.com/a/10984878/809705
     arr = np.array(arr, copy=copy, order="C")
     dtype = "S" + str(arr.shape[-1])
     return arr.view(dtype).reshape(arr.shape[:-1])

xarray/core/common.py

@@ -352,7 +352,7 @@ def __dir__(self) -> list[str]:
 
     def _ipython_key_completions_(self) -> list[str]:
         """Provide method for the key-autocompletions in IPython.
-        See http://ipython.readthedocs.io/en/stable/config/integrating.html#tab-completion
+        See https://ipython.readthedocs.io/en/stable/config/integrating.html#tab-completion
         For the details.
         """
         items = {