/
tonne_miles_breakdown.py
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/
tonne_miles_breakdown.py
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"""
Try me out in your browser:
[](https://mybinder.org/v2/gh/VorTECHsa/python-sdk/master?filepath=docs%2Fexamples%2Ftry_me_out%2Fton_miles_breakdown.ipynb)
"""
from typing import List, Union
from datetime import datetime
from vortexasdk.api import ID
from vortexasdk.endpoints.endpoints import TONNE_MILES_BREAKDOWN
from vortexasdk.operations import Search
from vortexasdk.utils import convert_to_list
from vortexasdk.api.shared_types import to_ISODate
from vortexasdk.endpoints.timeseries_result import TimeSeriesResult
class TonneMilesBreakdown(Search):
"""
The Tonne-miles Breakdown Endpoint is used to retrieve the tonne-miles data as a time series. The aggregation is done on the Vessel Movements data hence very similar search parameters are accepted (minus: `unit`, `size`, `offset`).
Additionally a parameter named `breakdown_frequency` can be used to specify the time series frequency.
A VesselMovement represents a single vessel moving between two locations.
The vessel may carry one cargo, many cargoes (co-loads), or zero cargos (ballast).
The start and end locations for a VesselMovement may be on land (loadings and discharges), they may be STS Zones (STS events), or they may be Floating Storage.
"""
def __init__(self):
Search.__init__(self, TONNE_MILES_BREAKDOWN)
def search(
self,
breakdown_frequency: str = None,
filter_time_min: datetime = datetime(2019, 10, 1, 0),
filter_time_max: datetime = datetime(2019, 10, 1, 1),
unit: str = "b",
filter_activity: str = None,
filter_charterers: Union[ID, List[ID]] = None,
filter_destinations: Union[ID, List[ID]] = None,
filter_origins: Union[ID, List[ID]] = None,
filter_owners: Union[ID, List[ID]] = None,
filter_products: Union[ID, List[ID]] = None,
filter_vessels: Union[ID, List[ID]] = None,
filter_vessel_classes: Union[ID, List[ID]] = None,
filter_vessel_status: str = None,
filter_vessel_age_min: int = None,
filter_vessel_age_max: int = None,
filter_vessel_dwt_min: int = None,
filter_vessel_dwt_max: int = None,
filter_vessel_scrubbers: str = "disabled",
filter_vessel_flags: Union[ID, List[ID]] = None,
filter_vessel_ice_class: Union[ID, List[ID]] = None,
filter_vessel_propulsion: Union[ID, List[ID]] = None,
exclude_origins: Union[ID, List[ID]] = None,
exclude_destinations: Union[ID, List[ID]] = None,
exclude_products: Union[ID, List[ID]] = None,
exclude_vessels: Union[ID, List[ID]] = None,
exclude_vessel_classes: Union[ID, List[ID]] = None,
exclude_charterers: Union[ID, List[ID]] = None,
exclude_owners: Union[ID, List[ID]] = None,
exclude_vessel_flags: Union[ID, List[ID]] = None,
exclude_vessel_ice_class: Union[ID, List[ID]] = None,
exclude_vessel_propulsion: Union[ID, List[ID]] = None,
) -> TimeSeriesResult:
"""
Find TonneMilesBreakdown matching the given search parameters.
# Arguments
breakdown_frequency: Must be one of: `'day'`, `'week'`, `'doe_week'`, `'month'`, `'quarter'` or `'year'`.
filter_activity: Movement activity on which to base the time filter. Must be one of: `'loading_state'`,
`'loading_start'`, `'loading_end'`, `'identified_for_loading_state'`, `'unloading_state'`, `'unloading_start'`,
`'unloading_end'`, `'unloaded_state'`, `'storing_state'`, `'storing_start'`, `'storing_end'`, `'transiting_state'`,
`'any_activity'`.
filter_time_min: The UTC start date of the time filter.
filter_time_max: The UTC end date of the time filter.
unit: Unit of measurement. Enter `'b'` for barrels or `'t'` for tonnes.
filter_charterers: A charterer ID, or list of charterer IDs to filter on.
filter_destinations: A geography ID, or list of geography IDs to filter on.
filter_origins: A geography ID, or list of geography IDs to filter on.
filter_owners: An corporation ID, or list of corporation IDs to filter on.
filter_products: A product ID, or list of product IDs to filter on.
filter_vessels: A vessel ID, or list of vessel IDs to filter on.
filter_vessel_classes: A vessel class, or list of vessel classes to filter on.
filter_vessel_status: The vessel status on which to base the filter. Enter `'vessel_status_ballast'` for ballast vessels, `'vessel_status_laden_known'` for laden vessels with known cargo (i.e. a type of cargo that Vortexa currently tracks) or `'vessel_status_laden_unknown'` for laden vessels with unknown cargo (i.e. a type of cargo that Vortexa currently does not track).
filter_vessel_age_min: A number between 1 and 100 (representing years).
filter_vessel_age_max: A number between 1 and 100 (representing years).
filter_vessel_dwt_min: A number representing minimum deadweight tonnage of a vessel.
filter_vessel_dwt_max: A number representing maximum deadweight tonnage of a vessel.
filter_vessel_scrubbers: Either inactive `'disabled'`, or included `'inc'` or excluded `'exc'`.
filter_vessel_flags: A geography ID, or list of geography IDs to filter on.
filter_vessel_ice_class: An attribute ID, or list of attribute IDs to filter on.
filter_vessel_propulsion: An attribute ID, or list of attribute IDs to filter on.
exclude_origins: A geography ID, or list of geography IDs to exclude.
exclude_destinations: A geography ID, or list of geography IDs to exclude.
exclude_products: A product ID, or list of product IDs to exclude.
exclude_vessels: A vessel ID, or list of vessel IDs to exclude.
exclude_vessel_classes: A vessel class, or list of vessel classes to exclude.
exclude_charterers: A charterer ID, or list of charterer IDs to exclude.
exclude_owners: An owner ID, or list of owner IDs to exclude.
exclude_vessel_flags: A geography ID, or list of geography IDs to exclude.
exclude_vessel_ice_class: An attribute ID, or list of attribute IDs to exclude.
exclude_vessel_propulsion: An attribute ID, or list of attribute IDs to exclude.
# Returns
`TimeSeriesResult`
# Example
```python
>>> from vortexasdk import TonneMilesBreakdown, Vessels
>>> from datetime import datetime
>>> new_wisdom = [g.id for g in Vessels().search("NEW WISDOM").to_list()]
>>> search_result = TonneMilesBreakdown().search(
... unit='b',
... breakdown_frequency='month',
... filter_vessels=new_wisdom,
... filter_time_min=datetime(2018, 1, 1),
... filter_time_max=datetime(2018, 12, 31))
>>> df = search_result.to_df()
```
returns
| |key |value |count |
|-----:|:------------------------|:-----------|-----:|
|0 |2018-01-01 00:00:00+00:00|4.558499e+07|1 |
|1 |2018-02-01 00:00:00+00:00|4.393985e+07|1 |
|2 |2018-03-01 00:00:00+00:00|7.781776e+06|1 |
|3 |2018-04-01 00:00:00+00:00|8.041169e+07|1 |
|4 |2018-05-01 00:00:00+00:00|3.346161e+07|1 |
|5 |2018-06-01 00:00:00+00:00|5.731648e+07|1 |
|6 |2018-07-01 00:00:00+00:00|4.976054e+07|1 |
|7 |2018-08-01 00:00:00+00:00|3.022656e+06|1 |
|8 |2018-09-01 00:00:00+00:00|2.504909e+07|1 |
|9 |2018-10-01 00:00:00+00:00|6.269583e+07|1 |
|10 |2018-11-01 00:00:00+00:00|1.823642e+07|1 |
|11 |2018-12-01 00:00:00+00:00|3.137448e+07|1 |
"""
exclude_params = {
"filter_origins": convert_to_list(exclude_origins),
"filter_destinations": convert_to_list(exclude_destinations),
"filter_products": convert_to_list(exclude_products),
"filter_vessels": convert_to_list(exclude_vessels),
"filter_vessel_classes": convert_to_list(exclude_vessel_classes),
"filter_charterers": convert_to_list(exclude_charterers),
"filter_owners": convert_to_list(exclude_owners),
"filter_vessel_flags": convert_to_list(exclude_vessel_flags),
"filter_vessel_ice_class": convert_to_list(
exclude_vessel_ice_class
),
"filter_vessel_propulsion": convert_to_list(
exclude_vessel_propulsion
),
}
api_params = {
"breakdown_frequency": breakdown_frequency,
"filter_activity": filter_activity,
"filter_time_min": to_ISODate(filter_time_min),
"filter_time_max": to_ISODate(filter_time_max),
"unit": unit,
"filter_charterers": convert_to_list(filter_charterers),
"filter_owners": convert_to_list(filter_owners),
"filter_destinations": convert_to_list(filter_destinations),
"filter_origins": convert_to_list(filter_origins),
"filter_products": convert_to_list(filter_products),
"filter_vessels": convert_to_list(filter_vessels),
"filter_vessel_classes": convert_to_list(filter_vessel_classes),
"filter_vessel_status": filter_vessel_status,
"filter_vessel_age_min": filter_vessel_age_min,
"filter_vessel_age_max": filter_vessel_age_max,
"filter_vessel_dwt_min": filter_vessel_dwt_min,
"filter_vessel_dwt_max": filter_vessel_dwt_max,
"filter_vessel_scrubbers": filter_vessel_scrubbers,
"filter_vessel_flags": convert_to_list(filter_vessel_flags),
"filter_vessel_ice_class": convert_to_list(
filter_vessel_ice_class
),
"filter_vessel_propulsion": convert_to_list(
filter_vessel_propulsion
),
"exclude": exclude_params,
}
return TimeSeriesResult(super().search(**api_params))