# [Examples](@id example-py)
## Initialize HiGHS
HiGHS must be initialized before making calls to the HiGHS Python
library, and the examples below assume that it has been done
```python
import highspy
import numpy as np
h = highspy.Highs()
```
## Read a model
To read a model into HiGHS from a MPS files and (CPLEX) LP files pass the file name to `readModel`.
```python
# Read a model from MPS file model.mps
filename = 'model.mps'
status = h.readModel(filename)
print('Reading model file ', filename, ' returns a status of ', status)
filename = 'model.dat'
status = h.readModel(filename)
print('Reading model file ', filename, ' returns a status of ', status)
```
## Build a model
Build the model
```raw
minimize f = x0 + x1
subject to x1 <= 7
5 <= x0 + 2x1 <= 15
6 <= 3x0 + 2x1
0 <= x0 <= 4; 1 <= x1
```
Using the simplified interface, the model can be built as follows:
```python
x0 = h.addVariable(lb = 0, ub = 4)
x1 = h.addVariable(lb = 1, ub = 7)
h.addConstr(5 <= x0 + 2*x1 <= 15)
h.addConstr(6 <= 3*x0 + 2*x1)
h.minimize(x0 + x1)
```
Alternatively, the model can be built using the more general interface, which allows the user to specify the model in a more flexible way.
Firstly, one variable at a time, via a sequence of calls to `addVar` and `addRow`:s
```python
inf = highspy.kHighsInf
# Define two variables, first using identifiers for the bound values,
# and then using constants
lower = 0
upper = 4
h.addVar(lower, upper)
h.addVar(1, inf)
# Define the objective coefficients (costs) of the two variables,
# identifying the variable by index, and changing its cost from the
# default value of zero
cost = 1
h.changeColCost(0, cost)
h.changeColCost(1, 1)
# Define constraints for the model
#
# The first constraint (x1<=7) has only one nonzero coefficient,
# identified by variable index 1 and value 1
num_nz = 1
index = 1
value = 1
h.addRow(-inf, 7, num_nz, index, value)
# The second constraint (5 <= x0 + 2x1 <= 15) has two nonzero
# coefficients, so arrays of indices and values are required
num_nz = 2
index = np.array([0, 1])
value = np.array([1, 2])
h.addRow(5, 15, num_nz, index, value)
# The final constraint (6 <= 3x0 + 2x1) has the same indices but
# different values
num_nz = 2
value = np.array([3, 2])
h.addRow(6, inf, num_nz, index, value)
# Access LP
lp = h.getLp()
num_nz = h.getNumNz()
print('LP has ', lp.num_col_, ' columns', lp.num_row_, ' rows and ', num_nz, ' nonzeros')
```
Alternatively, via calls to `addCols` and `addRows`.
```python
inf = highspy.kHighsInf
# The constraint matrix is defined with the rows below, but parameters
# for an empty (column-wise) matrix must be passed
cost = np.array([1, 1], dtype=np.double)
lower = np.array([0, 1], dtype=np.double)
upper = np.array([4, inf], dtype=np.double)
num_nz = 0
start = 0
index = 0
value = 0
h.addCols(2, cost, lower, upper, num_nz, start, index, value)
# Add the rows, with the constraint matrix row-wise
lower = np.array([-inf, 5, 6], dtype=np.double)
upper = np.array([7, 15, inf], dtype=np.double)
num_nz = 5
start = np.array([0, 1, 3])
index = np.array([1, 0, 1, 0, 1])
value = np.array([1, 1, 2, 3, 2], dtype=np.double)
h.addRows(3, lower, upper, num_nz, start, index, value)
```
* `passColName`
* `passRowName`
## Pass a model
Pass a model from a HighsLp instance
```python
inf = highspy.kHighsInf
# Define a HighsLp instance
lp = highspy.HighsLp()
lp.num_col_ = 2;
lp.num_row_ = 3;
lp.col_cost_ = np.array([1, 1], dtype=np.double)
lp.col_lower_ = np.array([0, 1], dtype=np.double)
lp.col_upper_ = np.array([4, inf], dtype=np.double)
lp.row_lower_ = np.array([-inf, 5, 6], dtype=np.double)
lp.row_upper_ = np.array([7, 15, inf], dtype=np.double)
# In a HighsLp instance, the number of nonzeros is given by a fictitious final start
lp.a_matrix_.start_ = np.array([0, 2, 5])
lp.a_matrix_.index_ = np.array([1, 2, 0, 1, 2])
lp.a_matrix_.value_ = np.array([1, 3, 1, 2, 2], dtype=np.double)
h.passModel(lp)
```
## Solve the model
The incumbent model in HiGHS is solved by calling
```python
h.run()
```
## Print solution information
```python
solution = h.getSolution()
basis = h.getBasis()
info = h.getInfo()
model_status = h.getModelStatus()
print('Model status = ', h.modelStatusToString(model_status))
print()
print('Optimal objective = ', info.objective_function_value)
print('Iteration count = ', info.simplex_iteration_count)
print('Primal solution status = ', h.solutionStatusToString(info.primal_solution_status))
print('Dual solution status = ', h.solutionStatusToString(info.dual_solution_status))
print('Basis validity = ', h.basisValidityToString(info.basis_validity))
```
!!! warning
The following are markers for documentation that has yet to be added
## Extract results
* `getModelStatus`
* `getInfo`
* `getSolution`
* `getBasis`
* `getObjectiveValue`
* `getDualObjectiveValue`
## Report results
* `writeSolution`
## [Option values](@id example-py-option-values)
* `setOptionValue`
* `getOptionValue`
## Get model data
* `getNumCol`
* `getNumRow`
* `getNumNz`
* `getCol`
* `getRow`
* `getColEntries`
* `getRowEntries`
* `getCols`
* `getRows`
* `getColsEntries`
* `getRowsEntries`
* `getColName`
* `getColByName`
* `getRowName`
* `getRowByName`
* `getCoeff`
## Modify model data
* `EnsureColwise`
* `EnsureRowwise`
* `changeObjectiveSense`
* `changeColCost`
* `changeColBounds`
* `changeRowBounds`
* `changeColsCost`
* `changeColsBounds`
* `changeRowsBounds`
* `changeCoeff`
## Set solution
* `setSolution`
## Set basis
* `setBasis`
## Presolve/postsolve
* `presolve`
* `getPresolvedLp`
* `getPresolvedModel`
* `getPresolveLog`
* `getPresolveOrigColsIndex`
* `getPresolveOrigRowsIndex`
* `getModelPresolveStatus`
* `writePresolvedModel`
* `presolveStatusToString`
* `presolveRuleTypeToString`
* `postsolve`
## Basis solves and tableau calculation
* `getBasicVariables`
* `getBasisInverseRow`
* `getBasisInverseRowSparse`
* `getBasisInverseCol`
* `getBasisInverseColSparse`
* `getBasisSolve`
* `getBasisSolveSparse`
* `getBasisTransposeSolve`
* `getBasisTransposeSolveSparse`
* `getReducedRow`
* `getReducedRowSparse`
* `getReducedColumn`
* `getReducedColumnSparse`
## Rays and unboundedness
* `getDualRayExist`
* `getDualRay`
* `getDualUnboundednessDirectionExist`
* `getDualUnboundednessDirection`
* `getPrimalRayExist`
* `getPrimalRay`
## Multi-objective optimization
* `addLinearObjective`
* `clearLinearObjectives`