[MNT] Extra dependency specifications per component (#5136)

Closes task 1 of #5101.

docs/source/developer_guide/dependencies.rst

@@ -58,8 +58,8 @@ Estimators with a soft dependency need to ensure the following:
    This prevents crashes for any users running ``check_estimator`` on all estimators, or a full local ``pytest`` run without the required soft dependency.
    See the tests in ``forecasting.tests.test_pmdarima`` for a concrete example.
 
-Adding a new soft dependency
-----------------------------
+Adding and maintaining soft dependencies
+----------------------------------------
 
 When adding a new soft dependency or changing the version of an existing one,
 the following need to be updated:
@@ -77,6 +77,22 @@ upper bounds on ``sktime`` core dependencies, or severe limitations to the user
 installation workflow.
 In such a case, it is strongly suggested not to add the soft dependency.
 
+For maintenance purposes, it has been decided that all soft-dependencies will have lower
+and upper bounds specified mandatorily. The soft-dependencies will be specified in
+separate extras per each component of ``sktime``, for example ``forecasting``,
+``classification``, ``regression``, etc. It is possible to have different upper and
+lower bounds for a single package when present in different extras, and can be modified in one without affecting the others.
+
+Upper bounds will be preferred to be set up as the next ``minor`` release of the
+packages, as ``patch`` updates should never contain breaking changes by convention of
+semantic versioning. For stable packages, next ``major`` verion can be used as well.
+
+Upper bounds will be automatically updated using ``dependabot``, which has been set up
+to run daily based on releases on ``PyPI``. The CI introducing newer upper bound will be
+merged into ``main`` branch only if all unit tests for the affected component(s) pass.
+
+Lower bounds maintenance planning is in progress and will be updated here soon.
+
 Adding a core or developer dependency
 -------------------------------------
 

pyproject.toml

@@ -53,6 +53,58 @@ dependencies = [
 ]
 
 [project.optional-dependencies]
+alignment = [
+    "dtw-python>=1.3,<1.4",
+    "numba>=0.53,<0.58",
+]
+annotation = [
+    "attrs>=23,<23.2",
+    "hmmlearn>=0.2.7,<0.4",
+    "numba>=0.53,<0.58",
+    "pyod>=0.8.0,<1.2",
+]
+classification = [
+    "esig>=0.9.7,<0.10",
+    "mrsqm>=0.0.3,<0.1",
+    "numba>=0.53,<0.58",
+    "tensorflow>=2,<=2.14",
+    "tsfresh>=0.17,<0.21",
+]
+clustering = [
+    "numba>=0.53,<0.58",
+    "tslearn>=0.5.2,<0.6.3",
+]
+forecasting = [
+    "pmdarima>=1.8,!=1.8.1,<2.1",
+    "prophet>=1.1,<1.2",
+    "statsforecast>=0.5.2,<1.6",
+    "statsmodels>=0.12.1,<0.15",
+    "tbats>=1.1,<1.2",
+]
+networks = [
+    "keras-self-attention>=0.51,<0.52",
+    "tensorflow>=2,<=2.14",
+]
+param_est = [
+    "seasonal>=0.3.1,<0.4",
+    "statsmodels>=0.12.1,<0.15",
+]
+regression = [
+    "numba>=0.53,<0.58",
+    "tensorflow>=2,<=2.14",
+]
+transformations = [
+    "esig>=0.9.7,<0.10",
+    "filterpy>=1.4.5,<1.5",
+    "holidays>=0.29,<0.32",
+    "mne>=1.5,<1.6",
+    "numba>=0.53,<0.58",
+    "pycatch22>=0.4,<0.5",
+    "pykalman>=0.9.5,<0.10",
+    "statsmodels>=0.12.1,<0.15",
+    "stumpy>=1.5.1,<1.13",
+    "tsfresh>=0.17,<0.21",
+]
 all_extras = [
     "attrs",
     "cloudpickle",