Merge upstream/master and fix copy() for new Constraint types

- Merge feat: add m.copy() method (PyPSA#623) from upstream
- Fix copy() to use MutableConstraint and .mutable() since the new
  Constraint class is CSR-backed and doesn't accept a Dataset constructor
- Fix objective value type: float() cast to satisfy float | None annotation

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Author: coroa

doc/api.rst

@@ -24,6 +24,7 @@ Creating a model
     piecewise.segments
     model.Model.linexpr
     model.Model.remove_constraints
+    model.Model.copy
 
 
 Classes under the hook

doc/release_notes.rst

@@ -4,6 +4,7 @@ Release Notes
 Upcoming Version
 ----------------
 
+* Add ``Model.copy()`` (default deep copy) with ``deep`` and ``include_solution`` options; support Python ``copy.copy`` and ``copy.deepcopy`` protocols via ``__copy__`` and ``__deepcopy__``.
 * Harmonize coordinate alignment for operations with subset/superset objects:
   - Multiplication and division fill missing coords with 0 (variable doesn't participate)
   - Addition and subtraction of constants fill missing coords with 0 (identity element) and pin result to LHS coords

linopy/io.py

@@ -1244,3 +1244,123 @@ def get_prefix(ds: xr.Dataset, prefix: str) -> xr.Dataset:
         setattr(m, k, ds.attrs.get(k))
 
     return m
+
+
+def copy(m: Model, include_solution: bool = False, deep: bool = True) -> Model:
+    """
+    Return a copy of this model.
+
+    With ``deep=True`` (default), variables, constraints, objective,
+    parameters, blocks, and scalar attributes are copied to a fully
+    independent model. With ``deep=False``, returns a shallow copy.
+
+    :meth:`Model.copy` defaults to deep copy for workflow safety.
+    In contrast, ``copy.copy(model)`` is shallow via ``__copy__``, and
+    ``copy.deepcopy(model)`` is deep via ``__deepcopy__``.
+
+    Solver runtime metadata (for example, ``solver_name`` and
+    ``solver_model``) is intentionally not copied. Solver backend state
+    is recreated on ``solve()``.
+
+    Parameters
+    ----------
+    m : Model
+        The model to copy.
+    include_solution : bool, optional
+        Whether to include solution and dual values in the copy.
+        If False (default), solve artifacts are excluded: solution/dual data,
+        objective value, and solve status are reset to initialized state.
+        If True, these values are copied when present. For unsolved models,
+        this has no additional effect.
+    deep : bool, optional
+        Whether to return a deep copy (default) or shallow copy. If False,
+        the returned model uses independent wrapper objects that share
+        underlying data buffers with the source model.
+
+    Returns
+    -------
+    Model
+        A deep or shallow copy of the model.
+    """
+    from linopy.constraints import Constraints, MutableConstraint
+    from linopy.expressions import LinearExpression
+    from linopy.model import Model, Objective
+    from linopy.variables import Variable, Variables
+
+    SOLVE_STATE_ATTRS = {"status", "termination_condition"}
+
+    new_model = Model(
+        chunk=m._chunk,
+        force_dim_names=m._force_dim_names,
+        auto_mask=m._auto_mask,
+        solver_dir=str(m._solver_dir),
+    )
+
+    new_model._variables = Variables(
+        {
+            name: Variable(
+                var.data.copy(deep=deep)
+                if include_solution
+                else var.data[m.variables.dataset_attrs].copy(deep=deep),
+                new_model,
+                name,
+            )
+            for name, var in m.variables.items()
+        },
+        new_model,
+    )
+
+    new_model._constraints = Constraints(
+        {
+            name: MutableConstraint(
+                con.mutable().data.copy(deep=deep)
+                if include_solution
+                else con.mutable().data[m.constraints.dataset_attrs].copy(deep=deep),
+                new_model,
+                name,
+            )
+            for name, con in m.constraints.items()
+        },
+        new_model,
+    )
+
+    obj_expr = LinearExpression(m.objective.expression.data.copy(deep=deep), new_model)
+    new_model._objective = Objective(obj_expr, new_model, m.objective.sense)
+    new_model._objective._value = (
+        float(m.objective.value)
+        if (include_solution and m.objective.value is not None)
+        else None
+    )
+
+    new_model._parameters = m._parameters.copy(deep=deep)
+    new_model._blocks = m._blocks.copy(deep=deep) if m._blocks is not None else None
+
+    for attr in m.scalar_attrs:
+        if include_solution or attr not in SOLVE_STATE_ATTRS:
+            setattr(new_model, attr, getattr(m, attr))
+
+    return new_model
+
+
+def shallowcopy(m: Model) -> Model:
+    """
+    Support Python's ``copy.copy`` protocol for ``Model``.
+
+    Returns a shallow copy with independent wrapper objects that share
+    underlying array buffers with ``m``. Solve artifacts are excluded,
+    matching :meth:`Model.copy` defaults.
+    """
+    return copy(m, include_solution=False, deep=False)
+
+
+def deepcopy(m: Model, memo: dict[int, Any]) -> Model:
+    """
+    Support Python's ``copy.deepcopy`` protocol for ``Model``.
+
+    Returns a deep, structurally independent copy and records it in ``memo``
+    as required by Python's copy protocol. Solve artifacts are excluded,
+    matching :meth:`Model.copy` defaults.
+    """
+    new_model = copy(m, include_solution=False, deep=True)
+    memo[id(m)] = new_model
+    return new_model

linopy/model.py

@@ -60,6 +60,9 @@
     ScalarLinearExpression,
 )
 from linopy.io import (
+    copy,
+    deepcopy,
+    shallowcopy,
     to_block_files,
     to_cupdlpx,
     to_file,
@@ -1920,6 +1923,12 @@ def reset_solution(self) -> None:
         self.variables.reset_solution()
         self.constraints.reset_dual()
 
+    copy = copy
+
+    __copy__ = shallowcopy
+
+    __deepcopy__ = deepcopy
+
     to_netcdf = to_netcdf
 
     to_file = to_file

test/test_model.py

@@ -5,15 +5,21 @@
 
 from __future__ import annotations
 
+import copy as pycopy
 from pathlib import Path
 from tempfile import gettempdir
 
 import numpy as np
 import pytest
 import xarray as xr
 
-from linopy import EQUAL, Model
-from linopy.testing import assert_model_equal
+from linopy import EQUAL, Model, available_solvers
+from linopy.testing import (
+    assert_conequal,
+    assert_equal,
+    assert_linequal,
+    assert_model_equal,
+)
 
 target_shape: tuple[int, int] = (10, 10)
 
@@ -164,3 +170,167 @@ def test_assert_model_equal() -> None:
     m.add_objective(obj)
 
     assert_model_equal(m, m)
+
+
+@pytest.fixture(scope="module")
+def copy_test_model() -> Model:
+    """Small representative model used across copy tests."""
+    m: Model = Model()
+
+    lower: xr.DataArray = xr.DataArray(
+        np.zeros((10, 10)), coords=[range(10), range(10)]
+    )
+    upper: xr.DataArray = xr.DataArray(np.ones((10, 10)), coords=[range(10), range(10)])
+    x = m.add_variables(lower, upper, name="x")
+    y = m.add_variables(name="y")
+
+    m.add_constraints(1 * x + 10 * y, EQUAL, 0)
+    m.add_objective((10 * x + 5 * y).sum())
+
+    return m
+
+
+@pytest.fixture(scope="module")
+def solved_copy_test_model(copy_test_model: Model) -> Model:
+    """Solved representative model used across solved-copy tests."""
+    m = copy_test_model.copy(deep=True)
+    m.solve()
+    return m
+
+
+def test_model_copy_unsolved(copy_test_model: Model) -> None:
+    """Copy of unsolved model is structurally equal and independent."""
+    m = copy_test_model.copy(deep=True)
+    c = m.copy(include_solution=False)
+
+    assert_model_equal(m, c)
+
+    # independence: mutating copy does not affect source
+    c.add_variables(name="z")
+    assert "z" not in m.variables
+
+
+def test_model_copy_unsolved_with_solution_flag(copy_test_model: Model) -> None:
+    """Unsolved model with include_solution=True has no extra solve artifacts."""
+    m = copy_test_model.copy(deep=True)
+
+    c_include_solution = m.copy(include_solution=True)
+    c_exclude_solution = m.copy(include_solution=False)
+
+    assert_model_equal(c_include_solution, c_exclude_solution)
+    assert c_include_solution.status == "initialized"
+    assert c_include_solution.termination_condition == ""
+    assert c_include_solution.objective.value is None
+
+
+def test_model_copy_shallow(copy_test_model: Model) -> None:
+    """Shallow copy has independent wrappers sharing underlying data buffers."""
+    m = copy_test_model.copy(deep=True)
+    c = m.copy(deep=False)
+
+    assert c is not m
+    assert c.variables is not m.variables
+    assert c.constraints is not m.constraints
+    assert c.objective is not m.objective
+
+    # wrappers are distinct, but shallow copy shares payload buffers
+    c.variables["x"].lower.values[0, 0] = 123.0
+    assert m.variables["x"].lower.values[0, 0] == 123.0
+
+
+def test_model_deepcopy_protocol(copy_test_model: Model) -> None:
+    """copy.deepcopy(model) dispatches to Model.__deepcopy__ and stays independent."""
+    m = copy_test_model.copy(deep=True)
+    c = pycopy.deepcopy(m)
+
+    assert_model_equal(m, c)
+
+    # Test independence: mutations to copy do not affect source
+    # 1. Variable mutation: add new variable
+    c.add_variables(name="z")
+    assert "z" not in m.variables
+
+    # 2. Variable data mutation (bounds): verify buffers are independent
+    original_lower = m.variables["x"].lower.values[0, 0].item()
+    new_lower = 999
+    c.variables["x"].lower.values[0, 0] = new_lower
+    assert c.variables["x"].lower.values[0, 0] == new_lower
+    assert m.variables["x"].lower.values[0, 0] == original_lower
+
+    # 3. Constraint coefficient mutation: deep copy must not leak back
+    original_con_coeff = m.constraints["con0"].coeffs.values.flat[0].item()
+    new_con_coeff = original_con_coeff + 42
+    c.constraints["con0"].coeffs.values.flat[0] = new_con_coeff
+    assert c.constraints["con0"].coeffs.values.flat[0] == new_con_coeff
+    assert m.constraints["con0"].coeffs.values.flat[0] == original_con_coeff
+
+    # 4. Objective expression coefficient mutation: deep copy must not leak back
+    original_obj_coeff = m.objective.expression.coeffs.values.flat[0].item()
+    new_obj_coeff = original_obj_coeff + 20
+    c.objective.expression.coeffs.values.flat[0] = new_obj_coeff
+    assert c.objective.expression.coeffs.values.flat[0] == new_obj_coeff
+    assert m.objective.expression.coeffs.values.flat[0] == original_obj_coeff
+
+    # 5. Objective sense mutation
+    original_sense = m.objective.sense
+    c.objective.sense = "max"
+    assert c.objective.sense == "max"
+    assert m.objective.sense == original_sense
+
+
+@pytest.mark.skipif(not available_solvers, reason="No solver installed")
+class TestModelCopySolved:
+    def test_model_deepcopy_protocol_excludes_solution(
+        self, solved_copy_test_model: Model
+    ) -> None:
+        """copy.deepcopy on solved model drops solve state by default."""
+        m = solved_copy_test_model
+
+        c = pycopy.deepcopy(m)
+
+        assert c.status == "initialized"
+        assert c.termination_condition == ""
+        assert c.objective.value is None
+
+        for v in m.variables:
+            assert_equal(
+                c.variables[v].data[c.variables.dataset_attrs],
+                m.variables[v].data[m.variables.dataset_attrs],
+            )
+        for con in m.constraints:
+            assert_conequal(c.constraints[con], m.constraints[con], strict=False)
+        assert_linequal(c.objective.expression, m.objective.expression)
+        assert c.objective.sense == m.objective.sense
+
+    def test_model_copy_solved_with_solution(
+        self, solved_copy_test_model: Model
+    ) -> None:
+        """Copy with include_solution=True preserves solve state."""
+        m = solved_copy_test_model
+
+        c = m.copy(include_solution=True)
+        assert_model_equal(m, c)
+
+    def test_model_copy_solved_without_solution(
+        self, solved_copy_test_model: Model
+    ) -> None:
+        """Copy with include_solution=False (default) drops solve state but preserves problem structure."""
+        m = solved_copy_test_model
+
+        c = m.copy(include_solution=False)
+
+        # solve state is dropped
+        assert c.status == "initialized"
+        assert c.termination_condition == ""
+        assert c.objective.value is None
+
+        # problem structure is preserved — compare only dataset_attrs to exclude solution/dual
+        for v in m.variables:
+            assert_equal(
+                c.variables[v].data[c.variables.dataset_attrs],
+                m.variables[v].data[m.variables.dataset_attrs],
+            )
+        for con in m.constraints:
+            assert_conequal(c.constraints[con], m.constraints[con], strict=False)
+        assert_linequal(c.objective.expression, m.objective.expression)
+        assert c.objective.sense == m.objective.sense