Release v0.6.10

Author: brynpickering

calliope/_version.py

@@ -1 +1 @@
-__version__ = "0.6.10-dev"
+__version__ = "0.6.10"

calliope/postprocess/plotting/flows.py

@@ -208,7 +208,7 @@ def _production_data(model, timesteps, timestep):
             techs_production = locs_techs_carriers_production.sel(
                 carriers=carrier, locs=location
             ).to_pandas()
-            for tech, prod in techs_production.loc[:, timestep].iteritems():
+            for tech, prod in techs_production.loc[:, timestep].items():
                 if prod and prod > 0:
                     # if some energy is at stake
 

changelog.rst

@@ -3,8 +3,8 @@
 Release History
 ===============
 
-0.6.10 (dev)
-------------
+0.6.10 (2023-01-18)
+-------------------
 
 |changed| |backwards-incompatible| Updated to Numpy v1.23, Pandas v1.5, Pyomo v6.4, Ruamel.yaml v0.17, Scikit-learn v1.2, Xarray v2022.3, GLPK v5. This enables Calliope to be installed on Apple Silicon devices, but changes the result of algorithmic timeseries clustering. `In scikit-learn version 0.24.0, the method of random sampling for K-Means clustering was changed <https://scikit-learn.org/stable/whats_new/v0.24.html#changed-models>`_. This change will lead to different optimisation results if using `K-Means clustering <https://calliope.readthedocs.io/en/v0.6.10/user/advanced_features.html#time-resolution-adjustment>`_ in your model.
 

doc/_static/notebooks/calliope_model_object.ipynb

@@ -36,7 +36,7 @@ Then install all development requirements for Calliope into a new environment, c
    $ conda env update -f requirements.yml -n calliope_dev # to install the calliope non-python dependencies and testing/coverage python packages
    $ conda env update -f requirements.txt -n calliope_dev # to install the pinned calliope python dependencies
    $ conda activate calliope_dev
-   $ pip install -e calliope
+   $ pip install -e . # installs from your local clone of the calliope repository
 
 Only calliope itself should be installed from pip, the rest will have been installed from conda and will be marked as `Requirement already satisfied` on running the above command.
 
@@ -257,13 +257,15 @@ Create release
 * Commit with message "Release vXXXX", then add a "vXXXX" tag, push both to GitHub
 * Create a release through the GitHub web interface, using the same tag, titling it "Release vXXXX" (required for Zenodo to pull it in)
 * Upload new release to PyPI: ``make all-dist``
-* Update the conda-forge package:
-    * Fork `conda-forge/calliope-feedstock <https://github.com/conda-forge/calliope-feedstock>`_, and update ``recipe/meta.yaml`` with:
-        * Version number: ``{% set version = "XXXX" %}``
-        * SHA256 of latest version from PyPI: ``{% set sha256 = "XXXX" %}``
-        * Reset ``build: number: 0`` if it is not already at zero
-        * If necessary, carry over any changed requirements from ``setup.py`` or ``requirements/base.yml``
-    * Submit a pull request from an appropriately named branch in your fork (e.g. ``vXXXX``) to the `conda-forge/calliope-feedstock <https://github.com/conda-forge/calliope-feedstock>`_ repository
+* Update the conda-forge package using the `Calliope feedstock <https://github.com/conda-forge/calliope-feedstock>`_:
+    * Wait for the the `regro-cf-autotick-bot` to open a pull request automatically (can take several hours)
+    * Check that ``recipe/meta.yaml`` in the pull request is up-to-date with:
+        * Version number: ``{% set version = "XXXX" %}`` (should be automatically updated)
+        * SHA256 of latest version from PyPI: ``{% set sha256 = "XXXX" %}`` (should be automatically updated)
+        * Reset ``build: number: 0`` if it is not already at zero (should be automatically updated)
+        * Range of python versions supported
+        * Requirement version pinning, to match any changes in ``requirements.txt`` and ``requirements.yml``
+    ^ Any necessary updates can be made direclty on the PR by pushing directly to the bot's branch or by using the GIthub interactive editing interface.
 
 Post-release
 ------------