Volume_flows History#
Returns historic versions of Leviaton’s LNG volumes transferred to specified terminals or countries over a given time period. The volume_flows endpoint calculates the LNG volume transferred to a set of destination terminals/countries (and optionally from a set of origin terminals/countries) for a given time range. For historical time periods this is simply the observed number of transactions that occurred at the destinations. For future time periods, forecasted volumes are calculated. Forecasted volumes are calculated using the route_score_weighted_volume field from the transactions/forecast endpoint. The route_score_weighted_volume is the volume of a potential transaction multiplied by the likelihood of that transaction occurring. Forecast volumes are the sum of the route_score_weighted_volume for the destinations in the given time period. Note that this means partial transactions are included in the forecast volume. Uncertainties in the forecast volume are estimated using our uncertainty in the forecast transaction timestamp.
Historical data:
Shows actual observed transaction volumes.
Forecasted data:
Predicts future volumes based on:
Potential vessel arrivals and their cargo volumes
Probability of each arrival occurring
Arrival time uncertainties
Endpoint#
POST |
https://leviaton.api.synmax.com/v1/volume_flows/history |
Python Method Name#
from synmax.leviaton.v1 import LeviatonApiClient
leviaton_client = LeviatonApiClient(access_token=access_token)
# Method name:
leviaton_api_client.volume_flows_history
Parameters#
Parameter |
Type |
Description |
Example |
|---|---|---|---|
destination_countries |
string |
A list of destination ISO 3166 country names to filter by. |
[‘Spain’, ‘USA’] |
destination_country_codes |
string |
A list of destination ISO 3166-1 alpha-2 country codes to filter by. |
[‘ES’, ‘US’] |
destination_polygons |
array |
A closed list of closed EPSG:4326 lon, lat coordinate pairs to filter by. |
[[[-125.0, 24.5], [-125.0, 49.5], [-66.9, 49.5], [-66.9, 24.5], [-125.0, 24.5]], [[122.9, 24.0], [122.9, 45.5], [146.0, 45.5], [146.0, 24.0], [122.9, 24.0]]] |
destination_regions |
string |
A list of destination regions to filter by. |
[‘Asia’, ‘Europe’] |
destination_terminals |
string |
A list of destination terminal names to filter by. |
[‘Sabine Pass’, ‘Mugardos R’] |
from_timestamp |
string |
The start UTC timestamp to filter by. |
2025-07-27T22:43:41.371622+00:00 |
loading_origin_countries |
string |
A list of loading origin ISO 3166 country names to filter by. |
[‘Malaysia’, ‘Japan’] |
loading_origin_country_codes |
string |
A list of loading origin ISO 3166-1 alpha-2 country codes to filter by. |
[‘MY’, ‘JP’] |
loading_origin_polygons |
array |
A closed list of closed EPSG:4326 lon, lat coordinate pairs to filter loading origin by. |
[[[99.6, 1.0], [99.6, 7.5], [104.5, 7.5], [104.5, 1.0], [99.6, 1.0]], [[109.0, 1.0], [109.0, 7.5], [115.0, 7.5], [115.0, 1.0], [109.0, 1.0]]] |
loading_origin_regions |
string |
A list of loading origin regions to filter by. |
[‘Asia’, ‘Europe’] |
loading_origin_terminals |
string |
A list of loading origin terminal names to filter by. |
[‘Chita’, ‘Sodeshi’, ‘MLNG’] |
to_timestamp |
string |
The end UTC timestamp to filter by. |
2025-07-27T22:43:41.371622+00:00 |
transaction_type |
string |
The type of transaction to filter by. |
loading |
Response Details#
Parameter |
Type |
Description |
Example |
|---|---|---|---|
count |
number |
The mean count of the volume of the forecasted flow. |
13.0 |
count_std |
number |
The standard deviation of the count of the volume of the forecasted flow. |
0.0 |
timestamp |
string |
The UTC timestamp of the forecasted flow. |
2025-07-27T22:43:41.371622+00:00 |
volume |
number |
The mean volume of the forecasted flow. |
41.011715 |
volume_std |
number |
The standard deviation of the volume of the forecasted flow. |
0.0 |
volume_unit |
string |
The unit of measurement for the forecasted volume. |
bcf |
Normal Output#
timestamp |
volume |
count |
volume_unit |
|---|---|---|---|
2019-12-31T00:00:00 |
61.093415 |
18 |
gas_Bcf |
2020-01-01T00:00:00 |
97.733045 |
31 |
gas_Bcf |
2020-01-02T00:00:00 |
53.58862478098315 |
26 |
gas_Bcf |
2020-01-03T00:00:00 |
126.8279923203463 |
40 |
gas_Bcf |
2020-01-04T00:00:00 |
93.48676671431649 |
33 |
gas_Bcf |
2020-01-05T00:00:00 |
95.34466989999999 |
34 |
gas_Bcf |
2020-01-06T00:00:00 |
121.44325526422618 |
40 |
gas_Bcf |
2020-01-07T00:00:00 |
77.07107540525806 |
32 |
gas_Bcf |
2020-01-08T00:00:00 |
120.62897864047619 |
45 |
gas_Bcf |
2020-01-09T00:00:00 |
112.5445267346628 |
42 |
gas_Bcf |