Python client for the KangRouter transportation service optimizer.

## Project description

[![Build Status](https://travis-ci.org/TheSolvingMachine/kangrouter-py.svg?branch=master)](https://travis-ci.org/TheSolvingMachine/kangrouter-py)

# kangrouter-py
Python client for [KangRouter](https://thesolvingmachine.com/kangrouter/) - pickup/delivery transportation services optimization.

## Installation

```bash
pip install kangrouter-py
```

## Usage

### Preliminaries
For interacting with the API, both an *apiKey* and a *licenseId* are required. Please
obtain them from your [account](https://thesolvingmachine.com/account) page.

### An example problem

Input problems are described as a python dict. As a (simplistic) example, consider the problem of:
* Taking [Alberto Caeiro](https://en.wikipedia.org/wiki/Fernando_Pessoa#Alberto_Caeiro) home after a medical appointment at the [Garcia de Orta Hospital](http://www.hgo.pt/). He is ready to leave the hospital after 13:00, and must be home no later than 14:15. Alberto is on a wheelchair, so we allocate 5 minutes for pickup and dropoff.
* Picking [Ricardo Reis](https://en.wikipedia.org/wiki/Fernando_Pessoa#Ricardo_Reis) at the [Brasileira](https://en.wikipedia.org/wiki/Caf%C3%A9_A_Brasileira) café, and take him to a beach restaurant. He wants to be there no later than 12:15. Ricardo takes a regular seat.

Assume that the vehicle available for transportation is parked in [Sintra](https://en.wikipedia.org/wiki/Sintra), has 3 seats and room for 2 wheelchairs. Additionally, the driver must have a 60 minute lunch break between 12:00 and 14:00.

This problem translates to the following object:

```python
problem = {
"nbResources": 2,
"jobs": [
{
"jobId": "Pickup Alberto at the hospital",
"origLat": "38.674921",
"origLon": "-9.175401",
"destLat": "38.716860",
"destLon": "-9.162417",
"minStartTime": "13:00",
"maxEndTime": "14:15",
"pickupDuration": 5,
"deliveryDuration": 5,
"consumptions": [0,1]
},
{
"jobId": "Take Ricardo to the beach",
"origLat": "38.710835",
"origLon": "-9.142143",
"destLat": "38.634080",
"destLon": "-9.230549",
"maxEndTime": "12:15",
"pickupDuration": 1,
"deliveryDuration": 1,
"consumptions": [1,0]
}
],
"vehicles": [
{
"vehicleId": "12-AS-46",
"depotLat": "38.806842",
"depotLon": "-9.382556",
"minStartTime": "07:00",
"maxEndTime": "22:00",
"maxWorkDuration": 540,
"capacities": [2,3],
"breaks": [
{
"breakId": "Lunch",
"minStartTime": "12:00",
"maxEndTime": "14:00",
"duration": 60
}
],
"overspeed": 1.25
}
]
}
```
Interesting problems have multiple jobs and multiple vehicles, but the example above should be enough to get you going.

### Submit a problem

The code below creates a new solver for the provided example:

```python
from kangrouter import KangRouterClient
solverId = api.create(problem)
```

### Check solving status

After a solver is created it can be in one of 4 states:
* pending - The solver is queued for execution but not started yet.
* solving - The solver is executing.
* completed - The solver has finished.
* invalid - The problem is invalid, or an unexpected error has occurred.

The function below is used to query the solver current state and obtain information regarding the solving progress:

```python
status = api.getStatus(solverId)
print(status)
```

This is a very simple problem, so the solver executes very quickly:

```python
{
"execStatus": "completed",
"solverEndTime": "Wed Nov 18 11:59:48 2015 GMT",
"solverStartTime": "Wed Nov 18 11:59:40 2015 GMT",
"totalDistance": 98,
}
```

Given that larger problems may take a few minutes, calling this function while the solver is executing will also return ETA (expected delivery time) for completion.

### Get the solution

When the solver is done, the solution may be retrieved as follows:

```python
solution = api.getSolution(solverId)
print(solution)
```

The solution shows at what times, or time intervals, drivers must leave their depots, start their work breaks, or perform pickup/delivery actions:

```python
{
"jobsScheduled": [
{
"jobId": "Pickup Alberto at the hospital",
"maxEndTime": "14:15",
"maxStartTime": "13:55",
"minEndTime": "13:20",
"minStartTime": "13:00",
"vehicleId": "12-AS-46"
},
{
"jobId": "Take Ricardo to the beach",
"maxEndTime": "12:15",
"maxStartTime": "11:59",
"minEndTime": "11:14",
"minStartTime": "10:58",
"vehicleId": "12-AS-46"
}
],
"type": "total",
"vehiclesScheduled": [
{
"breaks": [
{
"breakId": "Lunch",
"maxEndTime": "13:55",
"maxStartTime": "12:55",
"minEndTime": "13:00",
"minStartTime": "12:00"
}
],
"maxEndTime": "14:35",
"maxStartTime": "11:38",
"minEndTime": "13:40",
"minStartTime": "10:37",
"vehicleId": "12-AS-46"
}
]
}
```
### Other methods
The remaining methods allow to stop a running solver, which might be useful if you're in a hurry:

```python
api.stop(solverId)
```

and remove a solver (and associated data) from the server:

```python
api.delete(solverId)
```

* [KangRouter API Reference](https://thesolvingmachine.com/kangrouter/doc/en/)
* [KangRouter API Playground](https://thesolvingmachine.com/swagger/kangrouter/srv/)