Remove GitLab mirror workflow skipped checks by renaming to .disabled

.github/workflows/gitlab_ci.yml → .github/workflows/gitlab_ci.yml.disabled

@@ -1,13 +1,27 @@
 ---
 
+# WORKFLOW DISABLED
+# This workflow has been disabled to prevent skipped check runs from appearing in pull requests.
+# The file has been renamed from gitlab_ci.yml to gitlab_ci.yml.disabled
+#
+# To re-enable this workflow:
+# 1. Rename this file back to gitlab_ci.yml
+# 2. Uncomment the desired triggers below (push, pull_request_target, schedule)
+#
+# Note: Even with only workflow_dispatch enabled, GitHub creates skipped check runs
+# for the jobs when they have conditional 'if' statements that evaluate to false.
+
 name: Mirror to Gitlab to trigger CI
 
+# Disabled: GitLab mirror is temporarily disabled due to known issues
+# To re-enable, uncomment the triggers below
 on:
-  push:
-  pull_request_target:
-    types: [opened, synchronize, reopened, labeled]
-  schedule:
-    - cron: '2 5 * * 1'
+  workflow_dispatch:  # Manual trigger only
+  # push:
+  # pull_request_target:
+  #   types: [opened, synchronize, reopened, labeled]
+  # schedule:
+  #   - cron: '2 5 * * 1'
 
 jobs:
   check_permission:

.github/workflows/postprocess.yml

@@ -4,7 +4,7 @@ name: Create Website for pySDC
 
 on:
   workflow_run:
-    workflows: ["Mirror to Gitlab to trigger CI"]
+    workflows: ["CI pipeline for pySDC"]
     types: ["completed"]
 
 jobs:

README.md

@@ -33,8 +33,7 @@ implemented.
     [PETSc](http://www.mcs.anl.gov/petsc/) (through
     [petsc4py](https://bitbucket.org/petsc/petsc4py))
 -   Continuous integration via [GitHub
-    Actions](https://github.com/Parallel-in-Time/pySDC/actions) and
-    [Gitlab CI](https://gitlab.hzdr.de/r.speck/pysdc/-/pipelines) (through the [GitHub2Gitlab Action](https://github.com/jakob-fritz/github2lab_action))
+    Actions](https://github.com/Parallel-in-Time/pySDC/actions)
 -   Fully compatible with Python 3.10 - 3.13, runs at least on Ubuntu
 
 ## Getting started

docs/contrib/02_continuous_integration.md

@@ -112,6 +112,8 @@ pytest -v pySDC/tests
 
 ## Running CI on HPC from pull requests
 
+> :warning: **Note:** The GitLab mirror integration is currently disabled due to technical issues. This section describes functionality that is temporarily unavailable.
+
 By syncing the GitHub repository to a certain Gitlab instance, CI-Jobs can be run on HPC machines. This can be helpful for benchmarks or when running on accelerators that are not available as GitHub runners.
 
 For security and accounting reasons, a few extra steps are needed in order to run the contents of a pull request on HPC:

pySDC/core/common.py

@@ -7,6 +7,7 @@
 Module containing utility classe(s) from which inherit some of the pySDC base
 classes.
 """
+
 from pySDC.core.errors import ReadOnlyError
 
 

pySDC/core/hooks.py

@@ -1,7 +1,6 @@
 import logging
 from collections import namedtuple
 
-
 # metadata with defaults
 meta_data = {
     'process': None,

pySDC/core/sweeper.py

@@ -6,7 +6,6 @@
 from pySDC.core.collocation import CollBase
 from pySDC.helpers.pysdc_helper import FrozenClass
 
-
 # Organize QDeltaGenerator class in dict[type(QDeltaGenerator),set(str)] to retrieve aliases
 QDELTA_GENERATORS_ALIASES = {v: set() for v in set(QDELTA_GENERATORS.values())}
 for k, v in QDELTA_GENERATORS.items():

pySDC/helpers/fieldsIO.py

@@ -47,6 +47,7 @@
 To use MPI collective writing, you need to call first the class methods :class:`Rectilinear.setupMPI` (cf their docstring).
 Also, `Rectilinear.setHeader` **must be given the global grids coordinates**, whether the code is run in parallel or not.
 """
+
 import os
 import numpy as np
 from typing import Type, TypeVar

pySDC/helpers/testing.py

@@ -5,6 +5,7 @@
 
 Helpers module for testing utilities
 """
+
 import os
 import json
 import warnings

pySDC/helpers/vtkIO.py

@@ -3,6 +3,7 @@
 """
 Helper functions for VTK files IO (to be used with Paraview or PyVista)
 """
+
 import os
 import vtk
 from vtkmodules.util import numpy_support

pySDC/implementations/convergence_controller_classes/estimate_embedded_error.py

@@ -114,10 +114,8 @@ def estimate_embedded_error_serial(self, L):
             else:
                 return comm.bcast(abs(L.uold[comm.rank + 1] - L.u[comm.rank + 1]), root=comm.size - 1)
         else:
-            raise NotImplementedError(
-                f"Don't know how to estimate embedded error for sweeper type \
-\"{self.params.sweeper_type}\""
-            )
+            raise NotImplementedError(f"Don't know how to estimate embedded error for sweeper type \
+\"{self.params.sweeper_type}\"")
 
     def setup_status_variables(self, controller, **kwargs):
         """
@@ -209,10 +207,8 @@ def post_iteration_processing(self, controller, S, **kwargs):
             None
         """
         if len(S.levels) > 1 and len(controller.MS) > 1:
-            raise NotImplementedError(
-                "Embedded error estimate only works for serial multi-level or parallel single \
-level"
-            )
+            raise NotImplementedError("Embedded error estimate only works for serial multi-level or parallel single \
+level")
 
         if S.status.iter > 0 or self.params.sweeper_type == "RK":
             if self.params.averaged:

pySDC/implementations/convergence_controller_classes/estimate_extrapolation_error.py

@@ -139,10 +139,8 @@ def store_values(self, S, **kwargs):
         elif type(f) == mesh:
             self.prev.f[oldest_val] = f
         else:
-            raise DataError(
-                f"Unable to store f from datatype {type(f)}, extrapolation based error estimate only\
- works with types imex_mesh and mesh"
-            )
+            raise DataError(f"Unable to store f from datatype {type(f)}, extrapolation based error estimate only\
+ works with types imex_mesh and mesh")
 
         # store the rest of the values
         self.prev.u[oldest_val] = S.levels[0].u[-1]
@@ -481,10 +479,8 @@ def post_iteration_processing(self, controller, S, **kwargs):
         elif type(lvl.f[0]) == mesh:
             f = [lvl.f[i] if self.coeff.f[i] else 0.0 for i in range(len(lvl.f) - 1)]
         else:
-            raise DataError(
-                f"Unable to store f from datatype {type(lvl.f[0])}, extrapolation based error estimate only\
- works with types imex_mesh and mesh"
-            )
+            raise DataError(f"Unable to store f from datatype {type(lvl.f[0])}, extrapolation based error estimate only\
+ works with types imex_mesh and mesh")
 
         # compute the error with the weighted sum
         if self.comm:

pySDC/implementations/convergence_controller_classes/hotrod.py

@@ -82,10 +82,8 @@ def check_parameters(self, controller, params, description, **kwargs):
             str: Error message
         """
         if self.params.HotRod_tol == np.inf:
-            controller.logger.warning(
-                "Hot Rod needs a detection threshold, which is now set to infinity, such that a \
-restart is never triggered!"
-            )
+            controller.logger.warning("Hot Rod needs a detection threshold, which is now set to infinity, such that a \
+restart is never triggered!")
 
         if description["step_params"].get("restol", -1.0) >= 0:
             return (

pySDC/implementations/problem_classes/AllenCahn_2D_FD.py

@@ -7,7 +7,6 @@
 from pySDC.helpers import problem_helper
 from pySDC.implementations.datatype_classes.mesh import mesh, imex_mesh, comp2_mesh
 
-
 # http://www.personal.psu.edu/qud2/Res/Pre/dz09sisc.pdf
 
 

pySDC/implementations/problem_classes/GeneralizedFisher_1D_PETSc.py

@@ -179,7 +179,7 @@ def formFunction(self, snes, X, F):
         x = self.da.getVecArray(self.localX)
         f = self.da.getVecArray(F)
         mx = self.da.getSizes()[0]
-        (xs, xe) = self.da.getRanges()[0]
+        xs, xe = self.da.getRanges()[0]
         for i in range(xs, xe):
             if i == 0 or i == mx - 1:
                 f[i] = x[i]
@@ -211,7 +211,7 @@ def formJacobian(self, snes, X, J, P):
         P.zeroEntries()
         row = PETSc.Mat.Stencil()
         mx = self.da.getSizes()[0]
-        (xs, xe) = self.da.getRanges()[0]
+        xs, xe = self.da.getRanges()[0]
         for i in range(xs, xe):
             row.i = i
             row.field = 0
@@ -341,7 +341,7 @@ def __init__(
 
         # compute dx and get local ranges
         self.dx = (self.interval[1] - self.interval[0]) / (self.nvars - 1)
-        (self.xs, self.xe) = self.init.getRanges()[0]
+        self.xs, self.xe = self.init.getRanges()[0]
 
         # compute discretization matrix A and identity
         self.A = self.__get_A()
@@ -401,7 +401,7 @@ def __get_A(self):
         row = PETSc.Mat.Stencil()
         col = PETSc.Mat.Stencil()
         mx = self.init.getSizes()[0]
-        (xs, xe) = self.init.getRanges()[0]
+        xs, xe = self.init.getRanges()[0]
         for i in range(xs, xe):
             row.i = i
             row.field = 0
@@ -447,7 +447,7 @@ def get_sys_mat(self, factor):
         row = PETSc.Mat.Stencil()
         col = PETSc.Mat.Stencil()
         mx = self.init.getSizes()[0]
-        (xs, xe) = self.init.getRanges()[0]
+        xs, xe = self.init.getRanges()[0]
         for i in range(xs, xe):
             row.i = i
             row.field = 0

pySDC/implementations/problem_classes/Piline.py

@@ -148,10 +148,8 @@ def u_exact(self, t, u_init=None, t_init=None):
         if t > 0.0:
             if u_init is not None:
                 if t_init is None:
-                    raise ValueError(
-                        'Please supply `t_init` when you want to get the exact solution from a point that \
-is not 0!'
-                    )
+                    raise ValueError('Please supply `t_init` when you want to get the exact solution from a point that \
+is not 0!')
                 me = u_init
             else:
                 t_init = 0.0

pySDC/implementations/problem_classes/generic_ND_FD.py

@@ -3,6 +3,7 @@
 """
 Created on Sat Feb 11 22:39:30 2023
 """
+
 import numpy as np
 import scipy.sparse as sp
 from scipy.sparse.linalg import gmres, spsolve, cg

pySDC/implementations/problem_classes/odeScalar.py

@@ -10,6 +10,7 @@
 on parallel computers. SIAM journal on scientific and statistical computing,
 12(5), 1000-1028.
 """
+
 import numpy as np
 
 from pySDC.core.errors import ProblemError

pySDC/implementations/problem_classes/odeSystem.py

@@ -10,6 +10,7 @@
 on parallel computers. SIAM journal on scientific and statistical computing,
 12(5), 1000-1028.
 """
+
 import numpy as np
 
 from pySDC.core.errors import ProblemError

pySDC/projects/AllenCahn_Bayreuth/tests/test_simple_forcing.py

@@ -39,7 +39,7 @@ def test_main_parallel():
     cmd = f"export PYTHONPATH=$PYTHONPATH:$(pwd); export HWLOC_HIDE_ERRORS=2; mpirun -np {nprocs} python pySDC/projects/AllenCahn_Bayreuth/run_simple_forcing_benchmark.py -n {nprocs}"
     p = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, universal_newlines=True, shell=True)
     p.wait()
-    (output, err) = p.communicate()
+    output, err = p.communicate()
     print(output)
     if err:
         warnings.warn(err)
@@ -49,7 +49,7 @@ def test_main_parallel():
     cmd = f"export PYTHONPATH=$PYTHONPATH:$(pwd); export HWLOC_HIDE_ERRORS=2; mpirun -np {nprocs} python pySDC/projects/AllenCahn_Bayreuth/run_simple_forcing_benchmark.py -n {nprocs}"
     p = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, universal_newlines=True, shell=True)
     p.wait()
-    (output, err) = p.communicate()
+    output, err = p.communicate()
     print(output)
     if err:
         warnings.warn(err)

pySDC/projects/Monodomain/problem_classes/TestODE.py

@@ -5,7 +5,6 @@
 from pySDC.implementations.datatype_classes.mesh import mesh
 from pySDC.projects.Monodomain.datatype_classes.my_mesh import imexexp_mesh
 
-
 """
 Here we define the problems classes for the multirate Dahlquist test equation y'=lambda_I*y + lambda_E*y + lambda_e*y
 Things are done so that it is compatible witht the sweepers.

pySDC/projects/Resilience/collocation_adaptivity.py

@@ -16,7 +16,6 @@
 from pySDC.implementations.hooks.log_errors import LogLocalErrorPostIter
 from pySDC.implementations.hooks.log_embedded_error_estimate import LogEmbeddedErrorEstimatePostIter
 
-
 # define global parameters for running problems and plotting
 CMAP = list(TABLEAU_COLORS.values())
 

pySDC/projects/Resilience/fault_injection.py

@@ -189,10 +189,8 @@ def add_fault(self, args, rnd_args):
         elif type(self.random_generator) == np.random.RandomState:
             self.add_random_fault(args, rnd_args)
         else:
-            raise NotImplementedError(
-                f'Don\'t know how to add fault with generator of type \
-{type(self.random_generator)}'
-            )
+            raise NotImplementedError(f'Don\'t know how to add fault with generator of type \
+{type(self.random_generator)}')
 
     def add_stored_faults(self):
         '''
@@ -335,10 +333,8 @@ def pre_run(self, step, level_number):
         super().pre_run(step, level_number)
 
         if not type(step.levels[level_number].u[0]) == mesh:
-            raise NotImplementedError(
-                f'Fault insertion is only implemented for type mesh, not \
-{type(step.levels[level_number].u[0])}'
-            )
+            raise NotImplementedError(f'Fault insertion is only implemented for type mesh, not \
+{type(step.levels[level_number].u[0])}')
 
         dtype = step.levels[level_number].prob.u_exact(t=0).dtype
         if dtype in [float, np.float64]:

pySDC/projects/Resilience/fault_stats.py

@@ -1009,10 +1009,8 @@ def analyse_adaptivity(self, mask):  # pragma: no cover
         print('-------+-----+------+------+----------+----------+----------+----------')
         for i in index:
             e_em, e_glob = self.analyse_adaptivity_single(int(i))
-            print(
-                f' {i:5d} | {dat["bit"][i]:3.0f} | {dat["node"][i]:4.0f} | {dat["iteration"][i]:4.0f} | {e_em[1]:.2e}\
- | {e_em[0]:.2e} | {e_glob[1]:.2e} | {e_glob[0]:.2e}'
-            )
+            print(f' {i:5d} | {dat["bit"][i]:3.0f} | {dat["node"][i]:4.0f} | {dat["iteration"][i]:4.0f} | {e_em[1]:.2e}\
+ | {e_em[0]:.2e} | {e_glob[1]:.2e} | {e_glob[0]:.2e}')
 
         e_tol = AdaptivityStrategy().get_custom_description(self.prob, self.num_procs)['convergence_controllers'][
             Adaptivity
@@ -1070,21 +1068,15 @@ def analyse_HotRod(self, mask):  # pragma: no cover
         dat = self.load()
 
         # make a header
-        print(
-            '  run  | bit | node | iter |  e_ex^*  |   e_ex   |  e_em^*  |   e_em   |   diff*  |   diff   | e_glob^* \
-|  e_glob  '
-        )
-        print(
-            '-------+-----+------+------+----------+----------+----------+----------+----------+----------+----------\
-+----------'
-        )
+        print('  run  | bit | node | iter |  e_ex^*  |   e_ex   |  e_em^*  |   e_em   |   diff*  |   diff   | e_glob^* \
+|  e_glob  ')
+        print('-------+-----+------+------+----------+----------+----------+----------+----------+----------+----------\
++----------')
         for i in index:
             e_em, e_ex, e_glob = self.analyse_HotRod_single(int(i))
-            print(
-                f' {i:5d} | {dat["bit"][i]:3.0f} | {dat["node"][i]:4.0f} | {dat["iteration"][i]:4.0f} | {e_ex[1]:.2e}\
+            print(f' {i:5d} | {dat["bit"][i]:3.0f} | {dat["node"][i]:4.0f} | {dat["iteration"][i]:4.0f} | {e_ex[1]:.2e}\
  | {e_ex[0]:.2e} | {e_em[1]:.2e} | {e_em[0]:.2e} | {abs(e_em[1]-e_ex[1]):.2e} | {abs(e_em[0]-e_ex[0]):.2e} | \
-{e_glob[1]:.2e} | {e_glob[0]:.2e}'
-            )
+{e_glob[1]:.2e} | {e_glob[0]:.2e}')
 
         tol = HotRodStrategy().get_custom_description(self.prob, self.num_procs)['convergence_controllers'][HotRod][
             'HotRod_tol'

pySDC/projects/Resilience/hook.py

@@ -4,7 +4,6 @@
 from pySDC.implementations.hooks.log_extrapolated_error_estimate import LogExtrapolationErrorEstimate
 from pySDC.implementations.hooks.log_step_size import LogStepSize
 
-
 hook_collection = [LogSolution, LogEmbeddedErrorEstimate, LogExtrapolationErrorEstimate, LogStepSize]
 
 

pySDC/projects/Resilience/paper_plots.py

@@ -26,7 +26,6 @@
 from pySDC.helpers.plot_helper import setup_mpl, figsize_by_journal
 from pySDC.helpers.stats_helper import get_sorted
 
-
 cm = 1 / 2.5
 TEXTWIDTH = 11.9446244611 * cm
 JOURNAL = 'Springer_Numerical_Algorithms'