- Workers searching for shifts to apply for
- Filter and rank shifts based on the worker's travel time preferences
- Personalise shift listings with travel times from the worker's home address
- Enable workers to discover shifts that would previously have been missed using a straight-line distance search
- Show more relevant results leading to better matches, higher conversions, and fewer late arrivals and no-shows
- Improve the UX for workers with the information that they need to prevent them from bouncing to Google Maps to calculate travel times themselves
Reduced poor matches by 18%- Increased quality connection rate by 12%
- Reduced late withdrawals by 3x
Grisha Ghukasyan
VP of Engineering at Brigad
“In order to improve our financial benefits, we had to improve the connection rate...all the missions that we don't connect are lost - and we don't make any money on it.
Until we started working with TravelTime, all we showed was kilometres and straight-line distance, and it was making people leave the app.”
| Request type | POST |
| Host | api.traveltimeapp.com |
| Endpoint | /v4/time-filter |
| Authentication | Application-Id Api-Key |
{
"locations": [
{
"id": "Worker Home",
"coords": {
"lat": 54.2389,
"lng": -0.3975
}
},
{
"id": "Shift 1",
"coords": {
"lat": 54.2442,
"lng": -0.4075
}
},
{
"id": "Shift 2",
"coords": {
"lat": 5.2483,
"lng": -0.4349
}
},
.
.
.
{
"id": "Shift 2,000",
"coords": {
"lat": 53.9923,
"lng": -0.5134
}
}
],
"departure_searches": [
{
"id": "Shift Search",
"departure_location_id": "Worker Home",
"arrival_location_ids": [
"Shift 1",
"Shift 2",
.
.
.
"Shift 2,000"
],
"departure_time": "2024-10-01T19:00:00",
"travel_time": 14400,
"transportation": {
"type": "driving"
},
"properties": [
"travel_time"
]
}
]
}
locations - an array containing the IDs and lat-long coordinates of the worker's home location and all of the shifts. This can include up to 2,000 shifts, but could be pre-filtered using other relevant parameters if desired
departure_searches - travel times are calculated departing from the worker's home location, travelling to the different shift locations
departure_time - use the time that the worker will set off from home - could be the current time (if looking for immediate shifts) or a future time, such as "9am next Monday"
travel_time - used to filter the reachable listings based on the user's chosen commute time (up to 4 hours)
transportation - taken from the user's chosen transport mode, typically Driving / Public_Transport / Walking / Cycling
properties - the data point(s) to be calculated for each listing - typically just travel_time, but distance can also be used if required
{
"results": [
{
"search_id": "Shift Search",
"locations": [
{
"id": "Shift 2,000",
"properties": [
{
"travel_time": 3011
}
]
},
{
"id": "Shift 1",
"properties": [
{
"travel_time": 287
}
]
}
.
.
.
],
"unreachable": [
"Shift 2"
]
}
]
}
locations - Reachable listings based on the user's commute search parameters.
unreachable - Unreachable listings outside of the user's commute search parameters
npm i traveltime-apiThis package comes with TypeScript support.
Before starting, the package needs to be configured with your account's application ID and Key, which can be found in the TravelTime Developer Portal Dashboard. To create an instance - you will need to create new TravelTimeClient class object with credentials you got from dashboard.
import { TravelTimeClient } from 'traveltime-api';
const travelTimeClient = new TravelTimeClient({
apiKey: 'YOUR_APP_KEY',
applicationId: 'YOUR_APP_ID',
});
travelTimeClient.timeFilter({
"locations": [
{
"id": "Worker Home",
"coords": {
"lat": 54.2389,
"lng": -0.3975
}
},
{
"id": "Shift 1",
"coords": {
"lat": 54.2442,
"lng": -0.4075
}
},
{
"id": "Shift 2",
"coords": {
"lat": 5.2483,
"lng": -0.4349
}
},
.
.
.
{
"id": "Shift 2,000",
"coords": {
"lat": 53.9923,
"lng": -0.5134
}
}
],
"departure_searches": [
{
"id": "Shift Search",
"departure_location_id": "Worker Home",
"arrival_location_ids": [
"Shift 1",
"Shift 2",
.
.
.
"Shift 2,000"
],
"departure_time": "2024-10-01T19:00:00",
"travel_time": 14400,
"transportation": {
"type": "driving"
},
"properties": [
"travel_time"
]
}
]
}).then((data) => console.log(data))
.catch((e) => console.error(e));
Install Travel Time Python SDK in a virtualenv using pip. virtualenv is a tool to create isolated Python environments.
virtualenv allows to install Travel Time Python SDK without needing system install permissions, and without clashing with the installed system dependencies.
pip3 install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install traveltimepypip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install traveltimepyIn order to authenticate with Travel Time API, you will have to supply the Application Id and Api Key.
- app_id: str - Application Id
- api_key: str - Api Key
- limit_per_host: int - Number of simultaneous connections to one host.
- rate_limit: int - Number of searches which can be made in a time window.
- time_window: int - Duration, in seconds, of the time period in which to limit the rate.
- retry_attempts: int - Number of retries for failed requests.
- host: str - TravelTime host, default value is api.traveltimeapp.com.
- timeout: int - Maximum session time until timeout. Default value is 300 (5 minutes).
from traveltimepy import TravelTimeSdk
sdk = TravelTimeSdk(app_id="YOUR_APP_ID", api_key="YOUR_APP_KEY")
import asyncio
from traveltimepy import Location, Coordinates, Driving, Property, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
locations = [
Location(id="Worker Home", coords=Coordinates(lat=54.2389, lng=-0.3975)),
Location(id="Shift 1", coords=Coordinates(lat=54.2442, lng=-0.4075)),
Location(id="Shift 2", coords=Coordinates(lat=54.2483, lng=-0.4349)),
Location(id="Shift 3", coords=Coordinates(lat=53.9923, lng=-0.3134)),
.
.
.
Location(id="Shift 2,000", coords=Coordinates(lat=53.9923, lng=-0.5134))
]
results = await sdk.time_filter_async(
locations=locations,
search_ids={
"Worker Home": [
"Shift 1",
"Shift 2",
"Shift 3",
.
.
.
"Shift 2,000"
],
},
departure_time="2024-10-01T19:00:00",
travel_time=14400,
transportation=Driving(),
properties=[Property.TRAVEL_TIME],
)
print(results)
asyncio.run(main())
What is the performance like?
The Travel Time Matrix Fast endpoint can calculate 100,000 travel times in under 150ms.
How accurate is your data?
How reliable is the service?
Where do you have coverage?
How much will this cost?
We never charge based on usage. Instead we offer unlimited usage licences for a fixed monthly fee. The only thing you need to decide is the maximum Requests Per Minute (RPM) you need.
Can I test out the endpoint for myself?