Merge branch 'master' of github.com:materialsproject/pymatgen

Author: Shyue Ping Ong

.pre-commit-config.yaml

@@ -8,7 +8,7 @@ ci:
 
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.0.278
+    rev: v0.0.279
     hooks:
       - id: ruff
         args: [--fix]

ADMIN.md

@@ -9,10 +9,11 @@ The general procedure for releasing `pymatgen` comprises the following
 steps:
 
 1. Make sure all CI checks are green. We don't want to release known bugs.
-2. Update and edit changelog.
-3. Release PyPI versions + doc.
-4. Release `conda` versions.
-5. Release Dash documentation.
+1. Update changelog.
+1. Run `invoke make-doc` to update the HTML docs.
+1. Tag the latest commit with `git tag v<yyyy.mm.dd>`.
+1. Make a GitHub release with auto-generated release notes.
+1. Make sure the release action runs that publishes the new version to PyPI and conda-forge runs to completion.
 
 ## Initial setup
 
@@ -23,72 +24,29 @@ You will also need `sphinx` and `doc2dash`.
 pip install --upgrade invoke sphinx doc2dash
 ```
 
-Add your PyPI username and password and GITHUB_RELEASE_TOKEN into your
-environment:
-
-```sh
-export TWINE_USERNAME=PYPIUSERNAME
-export TWINE_PASSWORD=PYPIPASSWORD
-export GITHUB_RELEASES_TOKEN=TOKEN_YOU_GET_FROM_GITHUB
-```
-
-You may want to add these to your .bash_profile to avoid having to type
-these each time.
-
-### Machine-specific issues
-
-The above instructions are general, but some known issues are machine-specific:
-
-- Installing lxml via pip required <span
-  class="title-ref">STATIC_DEPS=true pip install lxml</span> on macOS
-  10.13.
-- It can be useful to <span class="title-ref">pip install --upgrade pip
-  twine setuptools</span> (this may be necessary if there are
-  authentication errors when connecting to PyPI).
-- You may have to <span class="title-ref">brew install hdf5
-  netcdf</span> or similar to be able to pip install the optional
-  requirement <span class="title-ref">netCDF4</span>.
-
 ## Doing the release
 
-Ensure appropriate environment variables are set including <span
-class="title-ref">DISCOURSE_API_USERNAME</span>, <span
-class="title-ref">DISCOURSE_API_KEY</span> and <span
-class="title-ref">GITHUB_RELEASES_TOKEN</span>.
-
-First update the change log. The autogenerated change log is simply a
-list of commit messages since the last version. Make sure to edit the
-log for brevity and to attribute significant features to appropriate
-developers:
+First update the change log. The autogenerated change log is simply a list of commit messages since the last version. Make sure to edit the log for brevity and to attribute significant features to appropriate developers:
 
 ```sh
 invoke update-changelog
 ```
 
-Then, do the release with the following sequence of commands (you can
-put them in a bash script in your PATH somewhere):
+Then, do the release with the following sequence of commands (you can put them in a bash script in your PATH somewhere):
 
 ```sh
 invoke release --notest --nodoc
 invoke update-doc
 python setup.py develop
 ```
 
-Double check that the releases are properly done on Pypi. If you are
-releasing on a Mac, you should see a pymatgen.version.tar.gz and two
-wheels (Py37 and P). There will be a py37 wheel for Windows that is
-generated by Appveyor.
+Double check that the releases are properly done on Pypi. If you are releasing on a Mac, you should see a pymatgen.version.tar.gz and two wheels (Py37 and P). There will be a py37 wheel for Windows that is generated by Appveyor.
 
 ## Materials.sh
 
-Fork and clone the
-[materials.sh](https://github.com/materialsvirtuallab/materials.sh).
-This repo contains the `conda` skeletons to build the `conda` versions for
-various matsci codes on the Anaconda [matsci
-channel](https://anaconda.org/matsci).
+Fork and clone the [materials.sh](https://github.com/materialsvirtuallab/materials.sh). This repo contains the `conda` skeletons to build the `conda` versions for various matsci codes on the Anaconda [matsci channel](https://anaconda.org/matsci).
 
-The first time this is run, you may need to <span class="title-ref">pip
-install beautifulsoup4</span>.
+The first time this is run, you may need to `pip install beautifulsoup4`.
 
 If you doing this for the first time, make sure conda-build and
 anaconda-client are installed:
@@ -114,16 +72,3 @@ versions.
 
 Check that the [matsci channel](https://anaconda.org/matsci) versions
 are properly updated.
-
-## Dash docs
-
-Fork and clone the [Dash User Contributions
-repo](https://github.com/Kapeli/Dash-User-Contributions).
-
-Generate the offline Dash doc using:
-
-```sh
-invoke contribute-dash
-```
-
-Create a pull request and submit.

CHANGES.rst

@@ -1,6 +1,13 @@
 Change log
 ==========
 
+- Unreadable string concat ops to f-string by @janosh in https://github.com/materialsproject/pymatgen/pull/3162
+- Revert `mp-api<0.34.0` pin by @janosh in https://github.com/materialsproject/pymatgen/pull/3165
+- Fix CI error `"pdentries_test.csv"` not found by @janosh in https://github.com/materialsproject/pymatgen/pull/3168
+- Fix issues with labels by @stefsmeets in https://github.com/materialsproject/pymatgen/pull/3169
+
+**Full Changelog**: https://github.com/materialsproject/pymatgen/compare/v2023.7.17...v2023.7.20
+
 v2023.7.17
 ----------
 - Cython 3.0 support.

dev_scripts/chemenv/equivalent_indices.py

@@ -133,5 +133,5 @@
             i7 = 6 if i0 in [1, 4] else 7
             equiv_list.append([i0, i1, i2, i3, i4, i5, i6, i7])
 
-    print(f"Equivalent indices ({len(equiv_list):d}) for {cg_symbol} : ")
+    print(f"Equivalent indices ({len(equiv_list)}) for {cg_symbol} : ")
     print(equiv_list)

dev_scripts/chemenv/explicit_permutations_plane_algorithm.py

@@ -36,14 +36,14 @@
 
     new_algos = []
 
-    ialgo = 1
+    idx = 1
     for sep_plane_algo in cg._algorithms:
-        print(f"In {ialgo = :d}/{len(cg._algorithms):d}")
-        ialgo += 1
+        print(f"In {idx = }/{len(cg._algorithms)}")
+        idx += 1
         if sep_plane_algo.algorithm_type != "SEPARATION_PLANE":
             raise ValueError("Should all be separation plane")
 
-        perms_on_file = f"Permutations on file in this algorithm ({len(sep_plane_algo._permutations):d}) "
+        perms_on_file = f"Permutations on file in this algorithm ({len(sep_plane_algo._permutations)}) "
         print(perms_on_file)
         print(sep_plane_algo._permutations)
         permutations = sep_plane_algo.safe_separation_permutations(
@@ -52,7 +52,7 @@
 
         sep_plane_algo._permutations = permutations
 
-        print(f"Test permutations ({len(permutations):d}) :")
+        print(f"Test permutations ({len(permutations)}) :")
         print(permutations)
 
         lgf = LocalGeometryFinder()
@@ -134,7 +134,7 @@
                 explicit_permutations.append(sep_perms[icsm])
 
         print(perms_on_file)
-        print(f"Permutations found ({len(explicit_permutations):d}) : ")
+        print(f"Permutations found ({len(explicit_permutations)}) : ")
         print(explicit_permutations)
         sep_plane_algo.explicit_permutations = explicit_permutations
         new_algos.append(sep_plane_algo)

dev_scripts/chemenv/get_plane_permutations_optimized.py

@@ -175,7 +175,7 @@ def random_permutations_iterator(initial_permutation, n_permutations):
         # 1. Check the algorithms defined for this coordination geometry and get the explicit permutations
         original_n_explicit_perms = []
         original_n_explicit_optimized_perms = []
-        for ialgo, algo in enumerate(cg.algorithms):
+        for idx, algo in enumerate(cg.algorithms):
             algo._permutations = algo.explicit_permutations
             algo.minimum_number_of_points = 4
             if algo.algorithm_type == "EXPLICIT_PERMUTATIONS":
@@ -185,7 +185,7 @@ def random_permutations_iterator(initial_permutation, n_permutations):
             else:
                 eop = str(len(algo.explicit_optimized_permutations))
             print(
-                f"For ialgo {ialgo,:d}, plane_points are "
+                f"For {idx=}, plane_points are "
                 f"[{', '.join(map(str, algo.plane_points))}], "
                 f"side_0 is [{', '.join(map(str, algo.point_groups[0]))}] and "
                 f"side_1 is [{', '.join(map(str, algo.point_groups[1]))}]."
@@ -194,7 +194,7 @@ def random_permutations_iterator(initial_permutation, n_permutations):
             original_n_explicit_optimized_perms.append(eop)
             print(
                 f"  For this algorithm, there are {eop} optimized permutations and "
-                f"{len(algo.explicit_permutations):d} explicit permutations"
+                f"{len(algo.explicit_permutations)} explicit permutations"
             )
             if algo.other_plane_points is None:
                 input("Multiplicity and other plane points is not defined for this algorithm !")
@@ -204,7 +204,7 @@ def random_permutations_iterator(initial_permutation, n_permutations):
                 ordered_plane=algo.ordered_plane, ordered_point_groups=algo.ordered_point_groups
             )
             algo._permutations = permutations
-            print(f"Safe permutations found ({len(permutations):d})")
+            print(f"Safe permutations found ({len(permutations)})")
 
             # Definition of the facets
             all_planes_point_indices = [algo.plane_points]
@@ -213,9 +213,9 @@ def random_permutations_iterator(initial_permutation, n_permutations):
 
             # Loop on the facets
             explicit_permutations_per_plane = []
-            for iplane, plane_point_indices in enumerate(all_planes_point_indices):
+            for idx_plane, plane_point_indices in enumerate(all_planes_point_indices):
                 prt1(
-                    string=f"In plane {iplane:d} ({'-'.join(str(pp) for pp in plane_point_indices)})",
+                    string=f"In plane {idx_plane} ({'-'.join(str(pp) for pp in plane_point_indices)})",
                     printing_volume=printing_volume,
                 )
 
@@ -268,7 +268,7 @@ def random_permutations_iterator(initial_permutation, n_permutations):
             algo.explicit_permutations = [list(perm) for perm in list(explicit_permutations_per_plane[0])]
             algo.explicit_permutations.sort()
             algo.explicit_permutations = np.array(algo.explicit_permutations)
-            print(f"Explicit permutations found ({len(algo.explicit_permutations):d})")
+            print(f"Explicit permutations found ({len(algo.explicit_permutations)})")
             print(algo.explicit_permutations)
             print()
             # Setup the permutations for the next optimization
@@ -291,10 +291,10 @@ def random_permutations_iterator(initial_permutation, n_permutations):
         perms_used_algos: list[dict] = [{} for _ in cg.algorithms]
 
         # Loop on algorithms
-        for ialgo, algo in enumerate(cg.algorithms):
+        for idx, algo in enumerate(cg.algorithms):
             perms_used: dict[tuple, int] = {}
             print(
-                f"In ialgo {ialgo:d} (plane_points : "
+                f"In {idx=} (plane_points : "
                 f"[{', '.join(map(str, algo.plane_points))}], "
                 f"side_0 : [{', '.join(map(str, algo.point_groups[0]))}] and "
                 f"side_1 : [{', '.join(map(str, algo.point_groups[1]))}])"
@@ -334,12 +334,12 @@ def random_permutations_iterator(initial_permutation, n_permutations):
                 raise ValueError("Permutation setup not allowed ...")
 
             # Loop on permutations
-            iperm = 1
+            idx_perm = 1
             t0 = time.process_time()
             time_left: float | str = "Unknown"
             for indices_perm in perms_iterator:
                 prt1(
-                    string=f"Perm # {iperm:d}/{n_permutations:d} : "
+                    string=f"Perm # {idx_perm}/{n_permutations} : "
                     f"{'-'.join(map(str, indices_perm))} "
                     f"(est. rem. time : {time_left} sec)",
                     printing_volume=printing_volume,
@@ -353,9 +353,9 @@ def random_permutations_iterator(initial_permutation, n_permutations):
 
                 # Loop on the facets
                 separation_permutations = []
-                for iplane, plane_point_indices in enumerate(all_planes_point_indices):
+                for idx_plane, plane_point_indices in enumerate(all_planes_point_indices):
                     prt2(
-                        string=f"In plane {iplane:d} ({'-'.join(str(pp) for pp in plane_point_indices)})",
+                        string=f"In plane {idx_plane} ({'-'.join(str(pp) for pp in plane_point_indices)})",
                         printing_volume=printing_volume,
                     )
 
@@ -399,28 +399,28 @@ def random_permutations_iterator(initial_permutation, n_permutations):
                     else:
                         perms_used[some_perm] = 1
                 tcurrent = time.process_time()
-                time_left = (n_permutations - iperm) * (tcurrent - t0) / iperm  # type: ignore
+                time_left = (n_permutations - idx_perm) * (tcurrent - t0) / idx_perm  # type: ignore
                 time_left = f"{time_left:.1f}"
-                iperm += 1
+                idx_perm += 1
             print(
-                f"Optimized permutations {len(perms_used):d}/{len(algo.permutations):d}"
-                f"(old : {original_n_explicit_optimized_perms[ialgo]}/{original_n_explicit_perms[ialgo]}) : "
+                f"Optimized permutations {len(perms_used)}/{len(algo.permutations)}"
+                f"(old : {original_n_explicit_optimized_perms[idx]}/{original_n_explicit_perms[idx]}) : "
             )
             for perm, number in perms_used.items():
-                print(f" - permutation {'-'.join(map(str, perm))} : {number:d}")
+                print(f" - permutation {'-'.join(map(str, perm))} : {number}")
             print(
-                f"For {ialgo=} (plane_points : [{', '.join(map(str, algo.plane_points))}], "
+                f"For {idx=} (plane_points : [{', '.join(map(str, algo.plane_points))}], "
                 f"side_0 : [{', '.join(map(str, algo.point_groups[0]))}] and "
                 f"side_1 : [{', '.join(map(str, algo.point_groups[1]))}]),\n"
                 f"Optimized perturbations {len(perms_used)}/{len(algo.permutations)} (old : "
-                f"{original_n_explicit_optimized_perms[ialgo]}/{original_n_explicit_perms[ialgo]}) are :"
+                f"{original_n_explicit_optimized_perms[idx]}/{original_n_explicit_perms[idx]}) are :"
             )
-            # print(f"Optimized permutations ({len(perms_used):d}/{len(algo.permutations):d}) : ")
+            # print(f"Optimized permutations ({len(perms_used)}/{len(algo.permutations)}) : ")
             explicit_optimized_permutations = [list(perm) for perm in perms_used]
             explicit_optimized_permutations.sort()
             print(explicit_optimized_permutations)
             print()
-            test = input(f'Set optimized permutations for algorithm {ialgo:d} ? ("y" to confirm)')
+            test = input(f'Set optimized permutations for algorithm {idx} ? ("y" to confirm)')
             if test == "y":
                 algo.explicit_optimized_permutations = np.array(explicit_optimized_permutations)
 

dev_scripts/chemenv/plane_multiplicity.py

@@ -30,5 +30,5 @@
             all_plane_points.append(tuple(equiv_plane))
         all_plane_points = [tuple(equiv_plane) for equiv_plane in set(all_plane_points)]
 
-    print(f"All plane points ({len(all_plane_points):d}) for {cg_symbol} : ")
+    print(f"All plane points ({len(all_plane_points)}) for {cg_symbol} : ")
     print(all_plane_points)

dev_scripts/chemenv/strategies/multi_weights_strategy_parameters.py

@@ -277,7 +277,7 @@ def get_weights(self, weights_options):
     for ii in range(1, 14):
         self_weight_max_csms_per_cn[str(ii)] = []
         for jj in range(ii + 1, 14):
-            cn_pair = f"{ii:d}_{jj:d}"
+            cn_pair = f"{ii}_{jj}"
             self_weight_max_csms[cn_pair] = []
             delta_csm_mins[cn_pair] = []
             all_cn_pairs.append(cn_pair)

dev_scripts/chemenv/test_algos.py

@@ -65,7 +65,7 @@
         lgf.perfect_geometry = AbstractGeometry.from_cg(cg=cg)
         points_perfect = lgf.perfect_geometry.points_wocs_ctwocc()
 
-        print(f"Perm # {idx_perm:d}/{n_perms:d} : ", indices_perm)
+        print(f"Perm # {idx_perm}/{n_perms} : ", indices_perm)
 
         algos_results = []
         for algo in cg.algorithms:

dev_scripts/chemenv/test_algos_all_geoms.py

@@ -98,7 +98,7 @@
                 lgf.perfect_geometry = AbstractGeometry.from_cg(cg=cg)
                 points_perfect = lgf.perfect_geometry.points_wocs_ctwocc()
 
-                print(f"Perm # {i_perm:d}/{n_perms:d} : ", indices_perm)
+                print(f"Perm # {i_perm}/{n_perms} : ", indices_perm)
 
                 algos_results = []
                 for algo in cg.algorithms: