Metadata-Version: 1.1
Name: docplex
Version: 2.10.150
Summary: The IBM Decision Optimization CPLEX Modeling for Python
Home-page: https://onboarding-oaas.docloud.ibmcloud.com/software/analytics/docloud/
Author: The IBM Decision Optimization on Cloud team
Author-email: dofeedback@wwpdl.vnet.ibm.com
License: 
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Description: DOcplex, IBM® Decision Optimization Modeling for Python
        =======================================================
        
        Welcome to the IBM® Decision Optimization CPLEX Modeling for Python.
        Licensed under the Apache License v2.0.
        
        With this library, you can quickly and easily add the power of optimization to
        your application. You can model your problems by using the Python API and solve
        them on the cloud with the IBM® Decision Optimization on Cloud service or on
        your computer with IBM® ILOG CPLEX Optimization Studio.
        
        This library is composed of 2 modules:
        
            * IBM® Decision Optimization CPLEX Optimizer Modeling for Python - with namespace docplex.mp
            * IBM® Decision Optimization CP Optimizer Modeling for Python - with namespace docplex.cp
        
        Solving with CPLEX locally requires that IBM® ILOG CPLEX Optimization Studio V12.8 or V12.9
        is installed on your machine.
        
        Solving with the IBM® Decision Optimization on Cloud service requires that you
        register for an account and get the API key.
        
        This library is `numpy` friendly.
        
        `Documentation <https://github.com/IBMDecisionOptimization/docplex-doc>`_
        
        `Examples <https://github.com/IBMDecisionOptimization/docplex-examples>`_
        
        Installation
        ------------
        
        *  ``pip install docplex``
        
        Changelog
        ---------
        
        Changed in 2.10.150:
        ````````````````````
        * In ``docplex.mp``:
           * fixed a bug in ModelReader when reading SAV files with no names
           * fixed a bug in mip starts, which prevented mip starts with piecewise
             functions to work properly.
           * fixed bug on Model.add_indicators() using comprehensions (len() was called).
           * Added support for the '!=' (not equals) operator in expressions.
           * Clarified four types of checker: on, off, numeric and full.
             Pass checker=<name> at model creation to specify which checker is used.
           * fixed a bug in solution JSON encoder for nonconvex QP problems.
           * Add direct support for lazy constraints, see Model.add_lazy_constraints()
           * Add direct support for user cuts, see Model.add_user_cut_constraints()
           * Get basis status of variables in LP problems, see `Var.basis_status`
           * Read MIP start files (MST format)
           * Allow to set the effort level for a MIP solution.
           * Read basis status files (in BAS format)
           * Read variable priority orders (in ORD format)
           * fixed bug in functional KPIs, solution argument was not passed on.
           * Enable constraint name dictionary at Model creation time: Model(cts_by_name=True)
           * Multi-objective is now pickled correctly
           * Multi-objective is now copied in Model.copy()
           * Wrote full documentation on progress listeners
           * Added `Model.set_lp_start_basis()` to provide an initial basis for LP problems.
        
             
        
        Changed in 2.9.141:
        ```````````````````
        
        * In ``docplex.mp``:
           * Removed links to rawgit.com as this service is going end of life.
           * Model.solve_lexicographic() is deprecated. This method should be used
             to perform lexicographic solve with COS 12.8, but with COS 12.9,
             Model.set_multi_objective() should be used for solving problems
             with multiple objectives.
        
        * In ``docplex.cp``:
           * Add KPIs supported by CPO Solver 12.9
           * Update CPO parser to read KPIs section for format 12.9
           * Add new examples with KPIs.
        
        
        Changed in 2.8.125:
        ```````````````````
        * Solving with solver agent 'docloud' is deprecated. 
          Models are now preferably solved with local solver, or the python source can be submitted to DOcplexcloud solve service. 
          See https://ibm.biz/BdYhhK.
        
        * In ``docplex.mp``:
           * solve_lexicographic is being deprecated. In a future version, a new api will be available to support multi-objectives.
        
        * In ``docplex.cp``:
           * Fix problem with boolean indicators in no_overlap(), always_constant() and always_equal().
           * Allow model solution to be used directly as a starting point (ignores what is not integer or interval var).
           * Add methods domain_min(), domain_max(), domain_iterator() and domain_contains() on both CpoIntVar and CpoIntVarSolution.
           * Default solver agent is now 'local' instead of 'docloud'. All examples modified consequently.
        
        
        Changed in 2.7.113:
        ```````````````````
        
        * In ``docplex.mp``:
           * Multiplying a constant expression by a quadratic expression raised an exception. Now returns the
             product of the quadratic expression and the constant value.
           * Model.solve_lexicographic() on cloud now send the previous pass solution as a MIP start (for MIP problems)
           * The slack of quadratic constraints always returned  zero. Now returns the correct value.
           * Accessing the dual (or slack) of a constraint that is not added to the model returned zero; now it raises an exception. A constraint must belong to a model to return a valid dual (or slack) value
           * Range constraints with infeasible domain (i.e. lb > ub) did not fail to solve. Now they raise a modeling exception.
           * Multiplying two absolute value expressions raised an exception. Now fixed.
           * When using tuples in variable dictionaries, the default name generation used to generate non-LP-compliant names,
             because of ( and ). Now the name generator formats the tuples with a "_" separator without parentheses.
        
        * In ``docplex.cp``:
           * Split fzn stuff in a separate package docplex.cp.fzn
           * Optimize construction of arrays in FZN parser
           * Enhance FZN parser and save 30% time
        
        
        Changed in 2.6.94:
        ``````````````````
        
        * In ``docplex.cp``:
           * Allow CpoModel.add() to accept list of constraints.
           * Fix a bug in the conversion of an array of boolean constants into CPO expression.
           * Extend CpoModel method set_parameters() to accept a dictionary and/or optional list of updates using named arguments.
           * Method CpoModel.set_parameters() now clone the CpoParameters object given in arguments.
           * Add a new method CpoModel.add_parameters() that updates parameters associated to the model.
           * Fix wrong source location (not in real model source) when CpoModel.add() is called from another docplex.cp method.
           * When constraint auto-naming is on (in particular for refine_conflict(), searchPhases are no more included in the process.
           * Parameters mean_UB and mean_LB are now optional in standard_deviation()
           * CpoModel.add() checks that the added expression is limited to constraint, boolean, objective or search phase.
           * Add documented functions slope_piecewise_linear() and coordinate__piecewise_linear() in modeler.py.
           * Remove default configuration settings for parameters TimeLimit and Workers.
        
        
        Changed in 2.5.92:
        ``````````````````
        
        * ``docplex.cli`` gains new features:
           * option ``--details`` will display solve details as they are published on
             DOcplexcloud.
           * options ``--url`` and ``-key`` allow specification of credentials without
             using a config file.
        
        * In ``docplex.cp``:
           * Fix problem with min() and max() that did not support optional key.
           * Add a Flatzinc parser capable of reading Minizinc Challenge problems.
           * Move expression dependencies analysis from model to compiler side.
           * No more constraint to have a unique name for model expressions. Compiler reallocate private names when needed.
           * Multiple variables or expressions with the same public name is now allowed.
           * Replace method CpoModel.get_expression() by CpoModel.get_named_expressions_dict().
           * Make SolverProgressPanelListener work properly with Python 2
           * Solve is automatically set to start/next loop when SolverProgressPanelListener is used.
           * In CpoModel, add a method that allows to substitute a function by another in the whole model.
           * Overwrite method __bool__ to avoid accidental use of CPO expressions as Python booleans.
           * Add special cases to search for the local CP Optimizer Interactive executable.
           * Allow methods min(), max(), min_of() and max_of() to support variable number of arguments.
           * Allow method all_diff() to support variable number of arguments.
           * Context parameter 'length_for_rename' is deprecated. Only length_for_alias is used.
           * Add a method add_var() in CpoModelSolution as a shortcut to add_integer_var_solution() and add_interval_var_solution()
           * Overwrite method __contains__() in CpoModelSolution to easily verify that a solution to a given variable is in the solution.
           * When called on a model, export_model() and get_cpo_string() disable all model optimization options.
        
        
        Changed in 2.4.61:
        ``````````````````
        
        * Both ``docplex.mp`` & ``docplex.cp``:
           * Support for CPLEX engines 12.8. Some features of docplex2.4 are available only with engines >= 12.8.
           * Adding new ports (AIX, plinux).
           * Examples are now available as Zeppelin notebooks.
        
        * In ``docplex.mp``:
           * Express a linear problem as a scikit-learn transformer by providing a numpy, a pandas or scipy matrix.
           * Logical constraints: constraint equivalence, if-then & rshift operator.
           * Meta-constraints: allow the use of discrete
             linear constraints in expressions, using their truth value.
           * Solve hook to add a method to be called at each intermediate solution.
           * KPIS automatically published at each intermediate solution if running on docplexcloud python worker.
           * Support for scipy coo & csr matrixes.
           * Fixed a bug in Model.add_constraints() when passing a string instead of a list of strings.
        
        * In ``docplex.cp``:
           * add new method run_seeds() to execute a model multiple times, available with local solver 12.8.
           * add support of new solver infos 'SearchStatus' and 'SearchStopCause'.
           * In method ``docplex.cp.model.CpoModel.propagate()``, add possibility to add an optional constraint to the model.
           * add domain iterator in integer variables and integer variables solutions, allowing to get domain
             as a list of individual integers.
           * add possibility to identify some model variables as KPIs of the model.
           * add abort_search() method on solver (not supported everywhere)
           * Rework code generation to enhance performances and remove unused variables that was pointed by removed expressions.
           * add possibility to add one or more CpoSolverListener to put some callback functions
             when solve is started, ended, or when a solution is found.
             Implementation is provided in new python module ``docplex.cp.solver.solver_listener`` that also contains sample
             listeners SolverProgressPanelListener and AutoStopListener.
           * Using parameter *context.solver.solve_with_start_next*, enable solve() method to execute a start/next loop instead
             of standard solve. This enables, for optimization problems, usage of SolveListeners with a greater progress accuracy.
           * Completely remove deprecated 'angel' to identify local solver.
           * Deprecate usage of methods ``minimize()`` and ``maximize()`` on ``docplex.cp.CpoModel``. 
           * Add methods ``get_objective_bounds()`` and ``get_objective_gaps()`` in solution objects.
        
          
          
        Changed in 2.3.44 (2017.09):
        ````````````````````````````
        
        * Module ``docplex.cp.model.solver_angel.py`` has been renamed ``solver_local.py``. 
          A shadow copy with previous name still exist to preserve ascending compatibility.
          Module ``docplex.cp.model.config.py`` is modified to refer this new module.
        * Class ``docplex.cp.model.solver_local.SolverAngel`` has been renamed ``SolverLocal``. 
          A shadow copy with previous name still exist to preserve ascending compatibility.
        * Class ``docplex.cp.model.solver_local.AngelException`` has been renamed ``LocalSolverException``. 
          A shadow copy with previous name still exist to preserve ascending compatibility.
        * Functions logical_and() and logical_or() are able to accept a list of model boolean expressions.
        * Fix defect on allowed_assignments() and forbiden_assignments() that was wrongly converting 
          list of tupes into tuple_set.
        * Update all examples to add comments and split them in sections data / prepare / model / solve
        * Add new sched_RCPSPMM_json.py example that reads data from JSON file instead of raw data file.
        * Rename all visu examples with more explicit names.
        * Remove the object class CpoTupleSet. Tuple sets can be constructed only by calling tuple_set() method, or more
          simply by passing directly a Python iterable of iterables when a tupleset is required 
          (in expressions allowed_assignments() and forbidden_assignments)
        * Allow logical_and() and logical_or() to accept a list of boolean expressions.
        * Add overloading of builtin functions all() and any() as other form of logical_and() and logical_or().
        * In no_overlap() and state_function(), transition matrix can be passed directly as a Python iterable of iterables of integers, 
        * Editable transition matrix, created with a size only, is deprecated. However it is still available for ascending compatibility.
        * Add conditional() modeling function
        * Parameter 'AutomaticReplay' is deprecated.
        * Add get_search_status() and get_stop_cause() on object CpoSolveResult, available for solver COS12.8
        * Improved performance of ``Var.reduced_cost()`` in ``docplex.mp``.
        
        Changed in 2.2.34 (2017.07):
        ````````````````````````````
        
        * Methods ``docplex.cp.model.export_model()`` and ``docplex.cp.model.import_model()``
          have been added to respectively generate or parse a model in CPO format.
        * Methods ``docplex.cp.model.minimize()`` and ``docplex.cp.model.maximize()``
          have been added to directly indicate an objective at model level.
        * Notebook example ``scheduling_tuto.ipynb`` contains an extensive tutorial
          to solve scheduling problems with CP.
        * Modeling method sum() now supports sum of cumul expressions.
        * Methods ``docplex.cp.model.start_search()`` allows to start a new 
          search sequence directly from the model object.
        * When setting ``context.solver.auto_publish`` is set, and using the CPLEX
          engine, KPIs and current objective are automatically published when the
          script is run on DOcplexcloud Python worker.
        * When setting ``context.solver.auto_publish`` is set, and using the CP
          engine, current objective is automatically published when the
          script is run on DOcplexcloud Python worker.
        * ``docplex.util.environment.Environment.set_stop_callback`` and
          ``docplex.util.environment.Environment.get_stop_callback`` are added so that
          you can add a callback when the DOcplexcloud job is aborted.
        
        
        Changed in 2.1.28:
        ``````````````````
        
        * New methods ``Model.logical_or()`` and ``Model.logical_and()`` handle
          logical operations on binary variables.
        * DOcplex now supports CPLEX 12.7.1 and Benders decomposition. Set annotations
          on constraints and variables using the ``benders_annotation`` property and use
          the proper CPLEX parameters governing Benders decomposition.
        * CPLEX tutorials: in the documentation and as notebooks in the examples.
        * Fixed a bug in ``docplex.mp.solution.SolveSolution.display()`` and in 
          ``docplex.mp.solution.Model.report_kpi()`` when using unicode variable names.
        * There's now a simple command line interface for DOcplexcloud. It can be run
          in a terminal. ``python -m docplex.cli help`` for more info. That command
          line reads your DOcplexcloud credentials in your cplex_config.py file. It
          allows you to submit, list, delete jobs on DOcplexcloud. The cli is available
          in notebooks too, using the ``%docplex_cli`` magics. ``%docplex_cli help`` for
          some help. In a notebook, credentials can be passed using `%docplex_url` and
          `%docplex_key` magics.
        * Removing constraints in 1 call
        * Bug fixes when editing an existing model.
        * Bug fix in the relaxation mechanism when using docplexcloud.
        
        
        Changed in 2.0.15:
        ``````````````````
        
        * Piecewise linear (PWL) functions are now supported. An API is now available
          on ``docplex.mp.model`` to create PWL functions and to create constraints using these PWL functions.
          PWL functions may be defined with breakpoints (default API) or by using slopes. Some simple arithmetic is
          also available to build new PWL functions by adding, subtracting, or scaling existing PWL functions.
        * DOcplex has undergone a significant overhaul effort that has resulted in an average of 30-50% improvement
          of modeling run-time performance. All parts of the API benefit from the performance improvements: creation of variables and constraints, removal of constraints, computation of sums of variables, and so on.
        * Constraints are now fully editable: 
          the expressions of a constraint can be modified.
          Similarly, the objective expression can also be modified. This allows for complex workflows in which the model is modified after a solve and then solved again. 
        * docplex is now available on Anaconda cloud and can be installed via the conda installation packager.
          See the `IBM Anaconda home <https://anaconda.org/IBMDecisionOptimization>`_
          CPLEX Community Edition for Python is also provided on Anaconda Cloud to get free local solving capabilities with limitations.
        * Support of ``~/.docplexrc`` configuration files for ``docplex.mp.context.Context`` is now dropped.
          This feature has been deprecated since 1.0.0.
        * Known incompatibility: class ``docplex.mp.model.AbstractModel`` moved to ``docplex.mp.absmodel.AbstractModel``. 
          Samples using this class have been updated.
        
        
        Changed in 1.0.630:
        ```````````````````
        
        * Added support for CPLEX 12.7 and Python 3.5.
        * Upgraded the DOcplexcloud client to version 1.0.202.
        * Module ``docplex.mp.advmodel`` is now officially supported. This module
          provides support for efficient, specialized aggregator methods for large
          models.
        * When solving on DOcplexcloud, proxies can now be specified with the
          ``context.solver.docloud.proxies`` property.
        * When two constraints are defined with the same name, issue a warning instead of
          a fatal exception. The last constraint defined will take over the first one in the name directory.
        * Fix ValueError when passing a pandas DataFrame as variable keys (using
          DataFrame indexes).
        * Solution.get_values() returns a collection of variable values in one call.
        * ``docplex.mp.model`` no longer imports ``docloud.status``. Any status
          previously initialized as ``JobSolveStatus.UNKNOWN`` is now initialized as
          ``None``.
        * Minor improvements to notebooks and examples.
        
        
Keywords: docloud,optimization,cplex,cpo
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
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Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
