class PuLPSolver(Solver):
LP_SOLVER = PULP_CBC_CMD(verbose=False, msg=False)
def __init__(self):
self.prob = LpProblem('Daily Fantasy Sports', LpMaximize)
def setup_solver(self):
pass
def add_variable(self, name, min_value=None, max_value=None):
if any([min_value, max_value]):
return LpVariable(name,
lowBound=min_value,
upBound=max_value,
cat=LpInteger)
return LpVariable(name, cat=LpBinary)
def set_objective(self, variables, coefficients):
self.prob += lpSum([
variable * coefficient
for variable, coefficient in zip(variables, coefficients)
])
def add_constraint(self, variables, coefficients, sign, rhs):
if coefficients:
lhs = [
variable * coefficient
for variable, coefficient in zip(variables, coefficients)
]
else:
lhs = variables
if sign == SolverSign.EQ:
self.prob += lpSum(lhs) == rhs
elif sign == SolverSign.NOT_EQ:
self.prob += lpSum(lhs) != rhs
elif sign == SolverSign.GTE:
self.prob += lpSum(lhs) >= rhs
elif sign == SolverSign.LTE:
self.prob += lpSum(lhs) <= rhs
else:
raise SolverException('Incorrect constraint sign')
def copy(self):
new_solver = type(self)()
new_solver.prob = self.prob.copy()
return new_solver
def solve(self):
self.prob.solve(self.LP_SOLVER)
if self.prob.status == LpStatusOptimal:
result = []
for variable in self.prob.variables():
val = variable.value()
if val is not None and round(val) >= 1.0:
result.append(variable)
return result
else:
raise SolverException('Unable to solve')
class PuLPSolver(Solver):
LP_SOLVER = PULP_CBC_CMD(threads=multiprocessing.cpu_count())
def __init__(self):
self.prob = None
def setup_solver(self):
self.prob = LpProblem('Daily Fantasy Sports', LpMaximize)
def add_variable(self, name):
return LpVariable(name, cat=LpBinary)
def set_objective(self, variables, coefficients):
self.prob += lpSum([
variable * coefficient
for variable, coefficient in zip(variables, coefficients)
])
def add_constraint(self, variables, coefficients, sign, rhs):
if coefficients:
lhs = [
variable * coefficient
for variable, coefficient in zip(variables, coefficients)
]
else:
lhs = variables
if sign == SolverSign.EQ:
self.prob += lpSum(lhs) == rhs
elif sign == SolverSign.NOT_EQ:
self.prob += lpSum(lhs) != rhs
elif sign == SolverSign.GTE:
self.prob += lpSum(lhs) >= rhs
elif sign == SolverSign.LTE:
self.prob += lpSum(lhs) <= rhs
else:
raise SolverException('Incorrect constraint sign')
def copy(self):
new_solver = type(self)()
new_solver.prob = self.prob.copy()
return new_solver
def solve(self):
self.prob.solve(self.LP_SOLVER)
if self.prob.status == LpStatusOptimal:
result = []
for variable in self.prob.variables():
if variable.value() == 1.0:
result.append(variable)
return result
else:
raise SolverException('Unable to solve')
class PuLPSolver(Solver):
def __init__(self):
self.prob = None
def setup_solver(self):
self.prob = LpProblem('Daily Fantasy Sports', LpMaximize)
def add_variable(self, name, low_bound, up_bound):
return LpVariable(name, low_bound, up_bound, LpInteger)
def set_objective(self, variables, coefficients):
self.prob += lpSum([
variable * coefficient
for variable, coefficient in zip(variables, coefficients)
])
def add_constraint(self, variables, coefficients, sign, rhs):
lhs = [
variable * coefficient
for variable, coefficient in zip(variables, coefficients)
]
if sign == SolverSign.EQ:
self.prob += lpSum(lhs) == rhs
elif sign == SolverSign.NOT_EQ:
self.prob += lpSum(lhs) != rhs
elif sign == SolverSign.GTE:
self.prob += lpSum(lhs) >= rhs
elif sign == SolverSign.LTE:
self.prob += lpSum(lhs) <= rhs
else:
raise SolverException('Incorrect constraint sign')
def copy(self):
new_solver = type(self)()
new_solver.prob = self.prob.copy()
return new_solver
def solve(self):
self.prob.solve()
if self.prob.status == LpStatusOptimal:
result = []
for variable in self.prob.variables():
if variable.value() == 1.0:
result.append(variable)
return result
else:
raise SolverException('Unable to solve')
class PuLPSolver(Solver):
LP_SOLVER = PULP_CBC_CMD(msg=False)
def __init__(self):
self.prob = LpProblem('pydfs_lineup_optimizer', LpMaximize)
def setup_solver(self):
pass
def add_variable(self, name, min_value=None, max_value=None):
name = name.replace(' ', '_')
if any([min_value, max_value]):
return LpVariable(name,
lowBound=min_value,
upBound=max_value,
cat=LpInteger)
return LpVariable(name, cat=LpBinary)
def set_objective(self, variables, coefficients):
self.prob += lpSum([
variable * coefficient
for variable, coefficient in zip(variables, coefficients)
])
def add_constraint(self, variables, coefficients, sign, rhs, name=None):
if coefficients:
lhs = [
variable * coefficient
for variable, coefficient in zip(variables, coefficients)
]
else:
lhs = variables
if sign == SolverSign.EQ:
self.prob += lpSum(lhs) == rhs, name
elif sign == SolverSign.NOT_EQ:
self.prob += lpSum(lhs) != rhs, name
elif sign == SolverSign.GTE:
self.prob += lpSum(lhs) >= rhs, name
elif sign == SolverSign.LTE:
self.prob += lpSum(lhs) <= rhs, name
else:
raise SolverException('Incorrect constraint sign')
def copy(self):
new_solver = type(self)()
new_solver.prob = self.prob.copy()
return new_solver
def solve(self):
self.prob.solve(self.LP_SOLVER)
if self.prob.status == LpStatusOptimal:
result = []
for variable in self.prob.variables():
val = variable.value()
if val is not None and round(val) >= 1.0:
result.append(variable)
return result
else:
invalid_constraints = [
(name or str(constraint))
for name, constraint in self.prob.constraints.items()
if not constraint.valid()
]
raise SolverInfeasibleSolutionException(invalid_constraints)