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        "author": "J.S. Roy and S.A. Mitchell",
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        "description": "Modifications Copyright (c) 2007- Stuart Anthony Mitchell (s.mitchell@auckland.ac.nz)\n\nPermission is hereby granted, free of charge, to any person obtaining a\ncopy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be included\nin all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS\nOR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n\nDescription: # pulp ![Build Status](https://travis-ci.org/coin-or/pulp.svg?branch=master)](https://travis-ci.org/coin-or/pulp)\n        \n        PuLP is an LP modeler written in python. PuLP can generate MPS or LP files\n        and call GLPK[1], COIN CLP/CBC[2], CPLEX[3], and GUROBI[4] to solve linear\n        problems.\n        \n        ## Installation\n        \n        The easiest way to install pulp is via [PyPi](https://pypi.python.org/pypi/PuLP)\n        \n        If pip is available on your system\n        \n             $pip install pulp\n        \n        Otherwise follow the download instructions on the PyPi page\n        On Linux and OSX systems the tests must be run to make the default\n        solver executable.\n        \n             $sudo pulptest\n        \n        ## Examples\n        \n        See the examples directory for examples.\n        \n        PuLP requires Python >= 2.6.\n        \n        The examples use the default solver (cbc), to use other solvers they must be available.\n        \n        # Documentation\n        Documentation is found on https://pythonhosted.org/PuLP/.\n        \n        \n        Use LpVariable() to create new variables. To create a variable 0 <= x <= 3\n        \n             >>> x = LpVariable(\"x\", 0, 3)\n        \n        To create a variable 0 <= y <= 1\n        \n             >>> y = LpVariable(\"y\", 0, 1)\n        \n        Use LpProblem() to create new problems. Create \"myProblem\"\n        \n             >>> prob = LpProblem(\"myProblem\", LpMinimize)\n        \n        Combine variables to create expressions and constraints and add them to the\n        problem.\n        \n             >>> prob += x + y <= 2\n        \n        If you add an expression (not a constraint), it will\n        become the objective.\n        \n             >>> prob += -4*x + y\n        \n        To solve with the default included solver\n        \n             >>> status = prob.solve()\n        \n        To use another sovler to solve the problem.\n        \n             >>> status = prob.solve(GLPK(msg = 0))\n        \n        Display the status of the solution\n        \n             >>> LpStatus[status]\n             'Optimal'\n        \n        You can get the value of the variables using value(). ex:\n        \n             >>> value(x)\n             2.0\n        \n        Exported Classes:\n        \n        * LpProblem -- Container class for a Linear programming problem\n        * LpVariable -- Variables that are added to constraints in the LP\n        * LpConstraint -- A constraint of the general form\n        \n              a1x1+a2x2 ...anxn (<=, =, >=) b\n        \n        *  LpConstraintVar -- Used to construct a column of the model in column-wise modelling\n        \n        Exported Functions:\n        \n        * value() -- Finds the value of a variable or expression\n        * lpSum() -- given a list of the form [a1*x1, a2x2, ..., anxn] will construct a linear expression to be used as a constraint or variable\n        * lpDot() --given two lists of the form [a1, a2, ..., an] and [ x1, x2, ..., xn] will construct a linear epression to be used as a constraint or variable\n        \n        Comments, bug reports, patches and suggestions are welcome.\n        pulp-or-discuss@googlegroups.com\n        \n             Copyright J.S. Roy (js@jeannot.org), 2003-2005\n             Copyright Stuart A. Mitchell (stu@stuartmitchell.com)\n             See the LICENSE file for copyright information.\n        \n        References:\n        [1] http://www.gnu.org/software/glpk/glpk.html\n        [2] http://www.coin-or.org/\n        [3] http://www.cplex.com/\n        [4] http://www.gurobi.com/\n        \nKeywords: Optimization,Linear Programming,Operations Research\nPlatform: UNKNOWN\nClassifier: Development Status :: 5 - Production/Stable\nClassifier: Environment :: Console\nClassifier: Intended Audience :: Science/Research\nClassifier: License :: OSI Approved :: BSD License\nClassifier: Natural Language :: English\nClassifier: Programming Language :: Python\nClassifier: Topic :: Scientific/Engineering :: Mathematics\nDescription-Content-Type: text/markdown\n",
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