Research
Security News
Malicious npm Package Targets Solana Developers and Hijacks Funds
A malicious npm package targets Solana developers, rerouting funds in 2% of transactions to a hardcoded address.
Travel Time Python SDK helps users find locations by journey
time rather than using ‘as the crow flies’ distance.
Time-based searching gives users more opportunities for personalisation and delivers a more relevant search.
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 traveltimepy
pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install traveltimepy
In order to authenticate with Travel Time API, you will have to supply the Application Id and Api Key.
from traveltimepy import TravelTimeSdk
sdk = TravelTimeSdk(app_id="YOUR_APP_ID", api_key="YOUR_APP_KEY")
Given origin coordinates, find shapes of zones reachable within corresponding travel time.
import asyncio
from datetime import datetime
from traveltimepy import Driving, Coordinates, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.time_map_async(
coordinates=[Coordinates(lat=51.507609, lng=-0.128315), Coordinates(lat=51.517609, lng=-0.138315)],
arrival_time=datetime.now(),
transportation=Driving()
)
print(results)
asyncio.run(main())
import asyncio
from datetime import datetime
from traveltimepy import Driving, Coordinates, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.time_map_geojson_async(
coordinates=[Coordinates(lat=51.507609, lng=-0.128315), Coordinates(lat=51.517609, lng=-0.138315)],
arrival_time=datetime.now(),
transportation=Driving()
)
print(results)
asyncio.run(main())
import asyncio
from datetime import datetime
from traveltimepy import Driving, Coordinates, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
response = await sdk.time_map_wkt_async(
coordinates=[Coordinates(lat=51.507609, lng=-0.128315), Coordinates(lat=51.517609, lng=-0.138315)],
arrival_time=datetime.now(),
transportation=Driving()
)
response.pretty_print() # for a custom formatted response
print(response) # default Python print
asyncio.run(main())
import asyncio
from datetime import datetime
from traveltimepy import Driving, Coordinates, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
response = await sdk.time_map_wkt_no_holes_async(
coordinates=[Coordinates(lat=51.507609, lng=-0.128315), Coordinates(lat=51.517609, lng=-0.138315)],
arrival_time=datetime.now(),
transportation=Driving()
)
response.pretty_print() # for a custom formatted response
print(response) # default Python print
asyncio.run(main())
Given origin coordinates, find intersections of specified shapes.
import asyncio
from datetime import datetime
from traveltimepy import Driving, Coordinates, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.intersection_async(
coordinates=[Coordinates(lat=51.507609, lng=-0.128315), Coordinates(lat=51.517609, lng=-0.138315)],
arrival_time=datetime.now(),
transportation=Driving()
)
print(results)
asyncio.run(main())
Given origin coordinates, find unions of specified shapes.
Finds the union of specified shapes.
import asyncio
from datetime import datetime
from traveltimepy import Driving, Coordinates, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.union_async(
coordinates=[Coordinates(lat=51.507609, lng=-0.128315), Coordinates(lat=51.517609, lng=-0.138315)],
arrival_time=datetime.now(),
transportation=Driving()
)
print(results)
asyncio.run(main())
A very fast version of time_map()
. However, the request parameters are much more limited.
import asyncio
from traveltimepy import Coordinates, TravelTimeSdk
from traveltimepy.dto.requests.time_map_fast import Transportation
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.time_map_fast_async(
coordinates=[Coordinates(lat=51.507609, lng=-0.128315), Coordinates(lat=51.517609, lng=-0.138315)],
transportation=Transportation(type="driving+ferry"),
travel_time=900
)
print(results)
asyncio.run(main())
import asyncio
from traveltimepy import Coordinates, TravelTimeSdk
from traveltimepy.dto.requests.time_map_fast import Transportation
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.time_map_fast_geojson_async(
coordinates=[Coordinates(lat=51.507609, lng=-0.128315), Coordinates(lat=51.517609, lng=-0.138315)],
transportation=Transportation(type="driving+ferry"),
travel_time=900
)
print(results)
asyncio.run(main())
Given origin coordinates, find shapes of zones reachable within corresponding travel distance.
import asyncio
from datetime import datetime
from traveltimepy import Driving, Coordinates, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.distance_map_async(
coordinates=[Coordinates(lat=51.507609, lng=-0.128315), Coordinates(lat=51.517609, lng=-0.138315)],
arrival_time=datetime.now(),
transportation=Driving()
)
print(results)
asyncio.run(main())
Given origin and destination points filter out points that cannot be reached within specified time limit. Find out travel times, distances and costs between an origin and up to 2,000 destination points.
import asyncio
from datetime import datetime
from traveltimepy import Location, Coordinates, PublicTransport, Property, FullRange, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
locations = [
Location(id="London center", coords=Coordinates(lat=51.508930, lng=-0.131387)),
Location(id="Hyde Park", coords=Coordinates(lat=51.508824, lng=-0.167093)),
Location(id="ZSL London Zoo", coords=Coordinates(lat=51.536067, lng=-0.153596))
]
results = await sdk.time_filter_async(
locations=locations,
search_ids={
"London center": ["Hyde Park", "ZSL London Zoo"],
"ZSL London Zoo": ["Hyde Park", "London center"],
},
departure_time=datetime.now(),
travel_time=3600,
transportation=PublicTransport(type="bus"),
properties=[Property.TRAVEL_TIME],
range=FullRange(enabled=True, max_results=3, width=600)
)
print(results)
asyncio.run(main())
A very fast version of time_filter()
. However, the request parameters are much more limited.
import asyncio
from traveltimepy import Location, Coordinates, Transportation, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
locations = [
Location(id="London center", coords=Coordinates(lat=51.508930, lng=-0.131387)),
Location(id="Hyde Park", coords=Coordinates(lat=51.508824, lng=-0.167093)),
Location(id="ZSL London Zoo", coords=Coordinates(lat=51.536067, lng=-0.153596))
]
results = await sdk.time_filter_fast_async(
locations=locations,
search_ids={
"London center": ["Hyde Park", "ZSL London Zoo"],
"ZSL London Zoo": ["Hyde Park", "London center"],
},
transportation=Transportation(type="public_transport"),
one_to_many=False
)
print(results)
asyncio.run(main())
A fast version of time filter communicating using protocol buffers.
The request parameters are much more limited and only travel time is returned. In addition, the results are only approximately correct (95% of the results are guaranteed to be within 5% of the routes returned by regular time filter). This inflexibility comes with a benefit of faster response times (Over 5x faster compared to regular time filter) and larger limits on the amount of destination points.
import asyncio
from traveltimepy import ProtoCountry, Coordinates, ProtoTransportation, TravelTimeSdk, PropertyProto
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
travel_times = await sdk.time_filter_proto_async(
origin=Coordinates(lat=51.425709, lng=-0.122061),
destinations=[
Coordinates(lat=51.348605, lng=-0.314783),
Coordinates(lat=51.337205, lng=-0.315793)
],
transportation=ProtoTransportation.DRIVING_FERRY,
travel_time=7200,
country=ProtoCountry.UNITED_KINGDOM,
properties=[PropertyProto.DISTANCE],
)
print(travel_times)
asyncio.run(main())
Returns routing information between source and destinations.
import asyncio
from datetime import datetime
from traveltimepy import Location, Coordinates, PublicTransport, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
locations = [
Location(id="London center", coords=Coordinates(lat=51.508930, lng=-0.131387)),
Location(id="Hyde Park", coords=Coordinates(lat=51.508824, lng=-0.167093)),
Location(id="ZSL London Zoo", coords=Coordinates(lat=51.536067, lng=-0.153596))
]
results = await sdk.routes_async(
locations=locations,
search_ids={
"London center": ["Hyde Park", "ZSL London Zoo"],
"ZSL London Zoo": ["Hyde Park", "London center"],
},
transportation=PublicTransport(),
departure_time=datetime.now()
)
print(results)
asyncio.run(main())
Match a query string to geographic coordinates.
import asyncio
from traveltimepy import TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.geocoding_async(query="Parliament square", limit=30)
print(results.features)
asyncio.run(main())
Match a latitude, longitude pair to an address.
import asyncio
from traveltimepy import TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.geocoding_reverse_async(lat=51.507281, lng=-0.132120)
print(results.features)
asyncio.run(main())
Find reachable postcodes from origin (or to destination) and get statistics about such postcodes. Currently only supports United Kingdom.
import asyncio
from datetime import datetime
from traveltimepy import Coordinates, PublicTransport, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.postcodes_async(
coordinates=[Coordinates(lat=51.507609, lng=-0.128315)],
departure_time=datetime.now(),
transportation=PublicTransport()
)
print(results)
asyncio.run(main())
Find districts that have a certain coverage from origin (or to destination) and get statistics about postcodes within such districts. Currently only supports United Kingdom.
import asyncio
from datetime import datetime
from traveltimepy import Coordinates, PublicTransport, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.postcodes_districts_async(
coordinates=[Coordinates(lat=51.507609, lng=-0.128315)],
departure_time=datetime.now(),
transportation=PublicTransport()
)
print(results)
asyncio.run(main())
Find sectors that have a certain coverage from origin (or to destination) and get statistics about postcodes within such sectors. Currently only supports United Kingdom.
import asyncio
from datetime import datetime
from traveltimepy import Coordinates, PublicTransport, TravelTimeSdk, ZonesProperty
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.postcodes_sectors_async(
coordinates=[Coordinates(lat=51.507609, lng=-0.128315)],
departure_time=datetime.now(),
transportation=PublicTransport(),
properties=[ZonesProperty.TRAVEL_TIME_REACHABLE, ZonesProperty.TRAVEL_TIME_ALL]
)
print(results)
asyncio.run(main())
Returns information about currently supported countries.
It is useful when you have an application that can do searches in any country that we support, you can use Supported Locations to get the map name for a certain point and then use this endpoint to check what features are available for that map. That way you could show fares for routes in the maps that support it.
import asyncio
from traveltimepy import TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
results = await sdk.map_info_async()
print(results)
asyncio.run(main())
Find out what points are supported by our api. The returned map name for a point can be used to determine what features are supported.
import asyncio
from traveltimepy import Location, Coordinates, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
locations = [
Location(id="Kaunas", coords=Coordinates(lat=54.900008, lng=23.957734)),
Location(id="London", coords=Coordinates(lat=51.506756, lng=-0.12805)),
Location(id="Bangkok", coords=Coordinates(lat=13.761866, lng=100.544818)),
Location(id="Lisbon", coords=Coordinates(lat=38.721869, lng=-9.138549)),
]
results = await sdk.supported_locations_async(locations)
print(results.locations)
print(results.unsupported_locations)
asyncio.run(main())
In transportation.py you can find all implemented transportation types, their sub-parameters and their default values.
These examples don't apply to proto / fast endpoints. For more examples you can always refer to Unit Tests
from traveltimepy import Driving
transportation=Driving()
transportation=Driving(disable_border_crossing = True)
from traveltimepy import Walking
transportation=Walking()
from traveltimepy import Cycling
transportation=Cycling()
from traveltimepy import Ferry
transportation=Ferry()
transportation=Ferry(type="cycling+ferry")
transportation=Ferry(type="driving+ferry")
transportation=Ferry(type="cycling+ferry", boarding_time = 300)
from traveltimepy import DrivingTrain, MaxChanges
transportation=DrivingTrain()
transportation=DrivingTrain(
pt_change_delay = 300,
driving_time_to_station=1800,
parking_time=800,
walking_time=500,
max_changes=MaxChanges(enabled=True, limit=3)
)
from traveltimepy import PublicTransport, MaxChanges
transportation=PublicTransport() # type="public_transport" - any public transport
transportation=PublicTransport(type="train")
transportation=PublicTransport(type="bus")
transportation=PublicTransport(type="coach")
transportation=PublicTransport(
pt_change_delay = 300,
walking_time=500,
max_changes=MaxChanges(enabled=True, limit=3)
)
from traveltimepy import CyclingPublicTransport, MaxChanges
transportation=CyclingPublicTransport()
transportation=CyclingPublicTransport(
walking_time=500,
pt_change_delay = 300,
cycling_time_to_station=300,
parking_time=800,
boarding_time=300,
max_changes=MaxChanges(enabled=True, limit=3)
)
level_of_detail
can be used to specify how detailed the isochrone result should be.
For a more detailed description of how to use this parameter, you can refer to our API Docs
from traveltimepy import LevelOfDetail
# scale_type "simple"
level_of_detail=LevelOfDetail(scale_type="simple", level="lowest")
# scale_type "simple_numeric"
level_of_detail=LevelOfDetail(scale_type="simple_numeric", level=0)
# scale_type "coarse_grid"
level_of_detail=LevelOfDetail(scale_type="coarse_grid", square_size=600)
snapping
Adjusts the process of looking up the nearest roads from the departure / arrival points.
For a more detailed description of how to use this parameter, you can refer to our API Docs
from traveltimepy.dto.common import Snapping, SnappingAcceptRoads, SnappingPenalty
snapping=Snapping(
penalty=SnappingPenalty.ENABLED, # default
accept_roads=SnappingAcceptRoads.BOTH_DRIVABLE_AND_WALKABLE # default
)
snapping=Snapping(
penalty=SnappingPenalty.DISABLED,
accept_roads=SnappingAcceptRoads.ANY_DRIVABLE
)
FAQs
Python Interface to Travel Time.
We found that traveltimepy demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Research
Security News
A malicious npm package targets Solana developers, rerouting funds in 2% of transactions to a hardcoded address.
Security News
Research
Socket researchers have discovered malicious npm packages targeting crypto developers, stealing credentials and wallet data using spyware delivered through typosquats of popular cryptographic libraries.
Security News
Socket's package search now displays weekly downloads for npm packages, helping developers quickly assess popularity and make more informed decisions.