Merge branch 'master' of https://github.com/scipopt/PySCIPOpt into SOS-1-constraints

Author: Joao-Dionisio

.github/workflows/coverage.yml

@@ -40,8 +40,9 @@ jobs:
 
       - name: Install PySCIPOpt
         run: |
-          export CFLAGS="-O0 -ggdb" # disable compiler optimizations for faster builds
-          python -m pip install .
+          export CFLAGS="-O0 -ggdb -Wall -Wextra -Werror" # Debug mode. More warnings. Warnings as errors.
+          python -m pip install . -v 2>&1 | tee build.log
+          grep -i "warning" build.log || true
 
       - name: Run pyscipopt tests
         run: |

CHANGELOG.md

@@ -2,10 +2,35 @@
 
 ## Unreleased
 ### Added
-- Added support for SOS1-constraints
+- More support for AND-Constraints
+- Added support for knapsack constraints
+- Added isPositive(), isNegative(), isFeasLE(), isFeasLT(), isFeasGE(), isFeasGT(), isHugeValue(), and tests
+- Added SCIP_LOCKTYPE, addVarLocksType(), getNLocksDown(), getNLocksUp(), getNLocksDownType(), getNLocksUpType(), and tests
+- Added addMatrixConsIndicator(), and tests
+- Added SCIPvarMarkRelaxationOnly, SCIPvarIsRelaxationOnly, SCIPvarMarkDeletable, SCIPvarIsDeletable, and tests
+- Wrapped SCIPgetNLPBranchCands
+- Added getConsVals() to get coefficients of any linear type constraint
+- Generalized getLhs() and getRhs() to additionally support any linear type constraint
+- Added recipe for getting local constraints
+- Added enableDebugSol() and disableDebugSol() for controlling the debug solution mechanism if DEBUGSOL=true
+### Fixed
+- Raised an error when an expression is used when a variable is required
+- Fixed some compile warnings
+### Changed
+- MatrixExpr.sum() now supports axis arguments and can return either a scalar or MatrixExpr depending on the result dimensions
+### Removed
+
+## 5.5.0 - 2025.05.06
+### Added
+- Wrapped SCIPgetChildren and added getChildren and test (also test getOpenNodes) 
+- Wrapped SCIPgetLeaves, SCIPgetNLeaves, and added getLeaves, getNLeaves and test
+- Wrapped SCIPgetSiblings, SCIPgetNSiblings, and added getSiblings, getNSiblings and test
+- Wrapped SCIPdeactivatePricer, SCIPsetConsModifiable, and added deactivatePricer, setModifiable and test
 - Added getLinearConsIndicator
 - Added SCIP_LPPARAM, setIntParam, setRealParam, getIntParam, getRealParam, isOptimal, getObjVal, getRedcost for lpi
 - Added isFeasPositive
+- Added SCIP function SCIProwGetDualsol and wrapper getDualsol
+- Added SCIP function SCIProwGetDualfarkas and wrapper getDualfarkas
 ### Fixed
 - Fixed bug when accessing matrix variable attributes
 ### Changed

INSTALL.md

@@ -26,7 +26,7 @@ If installing SCIP from source or using PyPI with a python and operating system
 you need to specify the install location using the environment variable
 `SCIPOPTDIR`:
 
--   on Linux and OS X:\
+-   on Linux and MacOS:\
     `export SCIPOPTDIR=<path_to_install_dir>`
 -   on Windows:\
     `set SCIPOPTDIR=<path_to_install_dir>` (**cmd**, **Cmder**, **WSL**)\
@@ -45,8 +45,9 @@ contains the corresponding header files:
         > nlpi
         > ...
 
-Please note that some Mac configurations require adding the library installation path to `DYLD_LIBRARY_PATH` when using a locally installed version of SCIP.
+On MacOS, to ensure that the SCIP dynamic library can be located at runtime by PySCIPOpt, you should add your SCIP installation path to the ``DYLD_LIBRARY_PATH`` environment variable by running:
 
+`export DYLD_LIBRARY_PATH="<path_to_install_dir>/lib:$DYLD_LIBRARY_PATH"`
 
 When building SCIP from source using Windows it is highly recommended to use the [Anaconda Python
 Platform](https://www.anaconda.com/).
@@ -56,6 +57,15 @@ Installation from PyPI
 
     python -m pip install pyscipopt
 
+To avoid interfering with system packages, it's best to use a [virtual environment](https://docs.python.org/3/library/venv.html).<br>
+<span style="color:orange">**Warning!**</span> This is mandatory in some newer configurations.
+
+```bash
+python3 -m venv venv source venv/bin/activate  # On Windows use: venv\Scripts\activate pip install pyscipopt
+pip install pyscipopt
+```
+Remember to activate the environment (`source venv/bin/activate`) in each terminal session where you use PySCIPOpt.
+
 Please note that if your Python version and OS version are in the combinations at the start of this INSTALL file then
 pip now automatically installs a pre-built version of SCIP. For these combinations, to use your own installation of SCIP,
 please see the section on building from source. For unavailable combinations this pip command will automatically
@@ -66,7 +76,7 @@ at runtime by adjusting your `PATH` environment variable:
 
 -   on Windows: `set PATH=%PATH%;%SCIPOPTDIR%\bin`
 
-On Linux and OS X this is encoded in the generated PySCIPOpt library and
+On Linux and MacOS this is encoded in the generated PySCIPOpt library and
 therefore not necessary.
 
 Building everything from source

README.md

@@ -23,10 +23,21 @@ See [CHANGELOG.md](https://github.com/scipopt/PySCIPOpt/blob/master/CHANGELOG.md
 Installation
 ------------
 
-The recommended installation method is via PyPI
+The recommended installation method is via [PyPI](https://pypi.org/project/PySCIPOpt/):
+
+```bash
+pip install pyscipopt
+```
+
+To avoid interfering with system packages, it's best to use a [virtual environment](https://docs.python.org/3/library/venv.html):
+
 ```bash
+python3 -m venv venv     # creates a virtual environment called venv
+source venv/bin/activate # activates the environment. On Windows use: venv\Scripts\activate
 pip install pyscipopt
 ```
+Remember to activate the environment (`source venv/bin/activate` or equivalent) in each terminal session where you use PySCIPOpt.
+Note that some configurations require the use of virtual environments.
 
 For information on specific versions, installation via Conda, and guides for building from source,
 please see the [online documentation](https://pyscipopt.readthedocs.io/en/latest/install.html).

RELEASE.md

@@ -1,16 +1,16 @@
 # Release Checklist
 The following are the steps to follow to make a new PySCIPOpt release. They should mostly be done in order. 
 - [ ] Check if [scipoptsuite-deploy](https://github.com/scipopt/scipoptsuite-deploy) needs a new release, if a new SCIP version is released for example, or new dependencies (change symmetry dependency, add support for papilo/ parallelization.. etc). And Update release links in `pyproject.toml`
-- [ ] Check if the table in [readme](https://github.com/scipopt/PySCIPOpt#installation) needs to be updated. 
+- [ ] Check if the table in the [documentation](https://pyscipopt.readthedocs.io/en/latest/build.html#building-from-source) needs to be updated. 
 - [ ] Update version number according to semantic versioning [rules](https://semver.org/) in `src/pyscipopt/_version.py` and `setup.py`
-- [ ] Update `CHANGELOG.md`; Change the `Unlreased` to the new version number and add an empty unreleased section.
+- [ ] Update `CHANGELOG.md`; Change the `Unreleased` to the new version number and add an empty unreleased section.
 - [ ] Create a release candidate on test-pypi by running the workflow “Build wheels” in Actions->build wheels, with these parameters `upload:true, test-pypi:true` 
 - [ ] If the pipeline passes, test the released pip package on test-pypi by running and checking that it works
 ```bash
 pip install -i https://test.pypi.org/simple/ PySCIPOpt
 ```
 - [ ] If it works, release on pypi.org with running the same workflow but with `test-pypi:false`.
-- [ ] Then create a tag wit the new version (from the master branch)
+- [ ] Then create a tag with the new version (from the master branch)
 ```bash
 git tag vX.X.X
 git push origin vX.X.X

docs/build.rst

@@ -100,6 +100,15 @@ For Linux and MacOS systems set the variable with the following command:
 
   export SCIPOPTDIR=<path_to_install_dir>
 
+.. note::
+
+  For macOS users, to ensure that the SCIP dynamic library can be found at runtime by PySCIPOpt,
+  you should add your SCIP installation path to the ``DYLD_LIBRARY_PATH`` environment variable by running:
+
+  .. code-block::
+
+    export DYLD_LIBRARY_PATH="<path_to_install_dir>/lib:$DYLD_LIBRARY_PATH"
+
 For Windows use the following command:
 
 .. code-block:: bash
@@ -159,8 +168,10 @@ Build with Debug
 To use debug information in PySCIPOpt you need to build it with the following command:
 
 .. code-block::
-
-  python -m pip install --install-option="--debug" .
+  
+  export CFLAGS="-UNDEBUG"
+  export CXXFLAGS="-UNDEBUG"
+  python -m pip install .
 
 .. note:: Be aware that you will need the debug library of the SCIP Optimization Suite for this to work
   (cmake .. -DCMAKE_BUILD_TYPE=Debug).

docs/extend.rst

@@ -44,7 +44,7 @@ Code contributions are very welcome and should comply to a few rules:
 - Before implementing a new PySCIPOpt feature, check whether the
   feature exists in SCIP. If so, implement it as a pure wrapper,
   mimicking SCIP whenever possible. If the new feature does not exist
-  in SCIP but it is close to an existing one, consider if implementing
+  in SCIP, but it is close to an existing one, consider if implementing
   that way is substantially convenient (e.g. Pythonic). If it does
   something completely different, you are welcome to pull your request
   and discuss the implementation.
@@ -77,7 +77,7 @@ API. By design, we distinguish different functions in PySCIPOPT:
 Ideally speaking, we want every SCIP function to be wrapped in PySCIPOpt.
 
 **Convenience functions** are additional, non-detrimental features meant
-to help prototyping the Python way. Since these functions are not in
+to help prototype the Python way. Since these functions are not in
 SCIP, we wish to limit them to prevent difference in features between
 SCIP and PySCIPOPT, which are always difficult to maintain. A few
 convenience functions survive in PySCIPOpt when keeping them is

docs/faq.rst

@@ -60,6 +60,6 @@ is not automatically deleted, and thus stops a new optimization call.
 Why can I not add a non-linear objective?
 =========================================
 
-SCIP does not support non-linear objectives, however, an equivalent optimization
+SCIP does not support non-linear objectives. However, an equivalent optimization
 problem can easily be constructed by introducing a single new variable and a constraint.
 Please see :doc:`this page <tutorials/expressions>` for a guide.

docs/install.rst

@@ -21,6 +21,20 @@ To install PySCIPOpt simply run the command:
 
   pip install pyscipopt
 
+To avoid interfering with system packages, it's best to use a `virtual environment <https://docs.python.org/3/library/venv.html>`.
+
+.. warning::
+
+  Using a virtual environment is **mandatory** in some newer Python configurations
+  to avoid permission and package conflicts.
+
+.. code-block:: bash
+python3 -m venv venv
+source venv/bin/activate  # On Windows use: venv\Scripts\activate
+pip install pyscipopt
+
+Remember to activate the environment (``source venv/bin/activate``) in each terminal session where you use PySCIPOpt.
+
 .. note:: For Linux users: PySCIPOpt versions newer than 5.1.1 installed via PyPI now require glibc 2.28+
 
   For our build infrastructure we use `manylinux <https://github.com/pypa/manylinux>`_.

docs/similarsoftware.rst

@@ -9,7 +9,7 @@ Alternate MIP Solvers (with Python interfaces)
 
 In the following we will give a list of other mixed-integer optimizers with available python interfaces.
 As each solver has its own set of problem classes that it can solve we will use a table with reference
-keys to summarise these problem classes.
+keys to summarize these problem classes.
 
 .. note:: This table is by no means complete.
 
@@ -87,8 +87,8 @@ This is software that is built on PySCIPOpt
 
 - `PyGCGOpt <https://github.com/scipopt/PyGCGOpt>`_: An extension of SCIP, using generic decompositions for solving MIPs
 - `GeCO <https://github.com/CharJon/GeCO>`_: Generators for Combinatorial Optimization
-- `scip-routing <https://github.com/mmghannam/scip-routing>`_:  An exact VRPTW solver in Python
-- `PySCIPOpt-ML <https://github.com/Opt-Mucca/PySCIPOpt-ML>`_:  Python interface to automatically formulate Machine Learning models into Mixed-Integer Programs
+- `scip-routing <https://github.com/mmghannam/scip-routing>`_: An exact VRPTW solver in Python
+- `PySCIPOpt-ML <https://github.com/Opt-Mucca/PySCIPOpt-ML>`_: Python interface to automatically formulate Machine Learning models into Mixed-Integer Programs
 -  `SCIP Book <https://scipbook.readthedocs.io/en/latest/>`_: Mathematical Optimization: Solving Problems using SCIP and Python
 
 Additional SCIP Resources