Free, intelligent routing for your logistics – now on Python
Project description
ElasticRoute for Python
API for solving large scale travelling salesman/fleet routing problems
You have a fleet of just 10 vehicles to serve 500 spots in the city. Some vehicles are only available in the day. Some stops can only be served at night. How would you solve this problem?
You don't need to. Just throw us a list of stops, vehicles and depots and we will do the heavy lifting for you. Routing as a Service!
BETA RELASE: ElasticRoute is completely free-to-use until 30th April 2020!
Quick Start Guide
Install with pip:
pip install elasticroute
In your code, set your default API Key (this can be retrieved from the dashboard of the web application):
import elasticroute as er
er.defaults.API_KEY = "my_super_secret_key"
Create a new Plan
object and givt it a name/id:
plan = er.Plan()
plan.id = "my_first_plan"
Give us an array of stops:
plan.stops = [
{
"name": "Changi Airport",
"address": "80 Airport Boulevard (S)819642",
},
{
"name": "Gardens By the Bay",
"lat": "1.281407",
"lng": "103.865770",
},
# add more stops!
# both human-readable addresses and machine-friendly coordinates work!
]
Give us an array of your available vehicles:
plan.vehicles = [
{
"name": "Van 1"
},
{
"name": "Van 2"
},
]
Give us an array of depots (warehouses):
plan.depots = [
{
"name": "Main Warehouse",
"address": "61 Kaki Bukit Ave 1 #04-34, Shun Li Ind Park Singapore 417943",
},
]
Set your country and timezone (for accurate geocoding):
plan.generalSettings["country"] = "SG"
plan.generalSettings["timezone"] = "Asia/Singapore"
Call solve()
and save the result to a variable:
solution = plan.solve()
Inspect the solution!
for stop in solution.stops:
print("Stop {} will be served by {} at time {}".format(stop["name"], stop["assign_to"], stop["eta"]))
Quick notes:
- The individual stops, vehicles and depots can be passed into the
Plan
as either dictionaries or instances ofelasticroute.Stop
,elasticroute.Vehicle
andelasticroute.Depot
respectively. Respective properties are the same as the dictionary keys. - Solving a plan returns you an instance of
elasticroute.Solution
, that has mostly the same properties aselasticroute.Plan
but not the same functions (see advanced usage) - Unlike when creating
Plan
's,Solution.stops|vehicles|depots
returns you instances ofelasticroute.Stop
,elasticroute.Vehicle
andelasticroute.Depot
accordingly instead of dictionaries.
Advanced Usage
Setting time constraints
Time constraints for Stops and Vehicles can be set with the from
and till
keys of elasticroute.Stop
and elasticroute.Vehicle
:
morning_only_stop = er.Stop()
morning_only_stop["name"] = "Morning Delivery 1"
morning_only_stop["from"] = 900
morning_only_stop["till"] = 1200
# add address and add to plan...
morning_shift_van = er.Vehicle()
morning_shift_van["name"] = "Morning Shift 1"
morning_shift_van["from"] = 900
morning_shift_van["till"] - 1200
# add to plan and solve...
Not specifying the from
and till
keys of either class would result it being defaulted to avail_from
and avail_to
keys in the elasticroute.defaults.generalSettings
dictionary, which in turn defaults to 500
and 1700
.
Setting home depots
A "home depot" can be set for both Stops and Vehicles. A depot for stops indicate where a vehicle must pick up a stop's goods before arriving, and a depot for vehicles indicate the start and end point of a Vehicle's journey (this implicitly assigns the possible jobs a Vehicle can take). By default, for every stop and vehicle, if the depot field is not specified we will assume it to be the first depot.
common_stop = er.Stop()
common_stop["name"] = "Normal Delivery 1"
common_stop["depot"] = "Main Warehouse"
# set stop address and add to plan...
rare_stop = er.Stop()
rare_stop["name"] = "Uncommon Delivery 1"
rare_stop["depot"] = "Auxillary Warehouse"
# set stop address and add to plan...
plan.vehicles = [
{
"name": "Main Warehouse Van",
"depot": "Main Warehouse"
},
{
"name": "Auxillary Warehouse Van",
"depot": "Auxillary Warehouse"
}
]
plan.depots = [
{
"name": "Main Warehouse",
"address": "Somewhere"
},
{
"name": "Auxillary Warehouse",
"address": "Somewhere else"
}
]
# solve and get results...
IMPORTANT: The value of the depot
fields MUST correspond to a matching elasticroute.Depot
in the same plan with the same name!
Setting load constraints
Each vehicle can be set to have a cumulative maximum weight, volume and (non-cumulative) seating capacity which can be used to determine how many stops it can serve before it has to return to the depot. Conversely, each stop can also be assigned weight, volume and seating loads.
The keys are weight_load
, volume_load
, seating_load
for Stops and weight_capacity
, volume_capacity
and seating_capacity
for Vehicles.
Alternative connection types (for large datasets)
By default, all requests are made in a synchronous manner. Most small to medium-sized datasets can be solved in less than 10 seconds, but for production uses you probably may one to close the HTTP connection first and poll for updates in the following manner:
import time
plan = er.Plan()
plan.connection_type = "poll";
# do the usual stuff
solution = plan.solve()
while solution.status != "planned":
solution.refresh()
time.sleep(2)
# or do some threading or promise
Setting the connection_type
to "poll"
will cause the server to return you a response immediately after parsing the request data. You can monitor the status with the status
and progress
properties while fetching updates with the refresh()
method.
In addition, setting the connectionType
to "webhook"
will also cause the server to post a copy of the response to your said webhook. The exact location of the webhook can be specified with the webhook
property of Plan
objects.
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