/
vessel_availability_breakdown.py
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/
vessel_availability_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%2Favailability_breakdown.ipynb)
"""
from typing import Any, List, Union, Dict
from vortexasdk.endpoints.timeseries_result import TimeSeriesResult
from vortexasdk.api import ID
from vortexasdk.endpoints.endpoints import (
VESSEL_AVAILABILITY_BREAKDOWN_RESOURCE,
)
from vortexasdk.api.shared_types import (
Tag,
)
from vortexasdk.logger import get_logger
from vortexasdk.operations import Search
from vortexasdk.utils import convert_to_list
logger = get_logger(__name__)
class VesselAvailabilityBreakdown(Search):
"""
Please note: you will require a subscription to our Freight module to access this endpoint.
"""
def __init__(self):
Search.__init__(self, VESSEL_AVAILABILITY_BREAKDOWN_RESOURCE)
def search(
self,
filter_products: Union[ID, List[ID]] = None,
filter_vessels: Union[ID, List[ID]] = None,
filter_vessel_classes: Union[str, List[str]] = None,
filter_vessel_status: str = None,
filter_vessel_location: Union[ID, List[ID]] = None,
filter_owners: Union[ID, List[ID]] = None,
filter_effective_controllers: Union[ID, List[ID]] = None,
filter_destination: Union[ID, List[ID]] = None,
filter_region: str = None,
filter_port: str = None,
use_reference_port: bool = False,
filter_days_to_arrival: List[Dict[str, int]] = None,
filter_vessel_dwt_min: int = None,
filter_vessel_dwt_max: int = None,
filter_vessel_age_min: int = None,
filter_vessel_age_max: int = None,
filter_vessel_idle_min: int = None,
filter_vessel_idle_max: int = None,
filter_vessel_scrubbers: str = "disabled",
filter_recent_visits: str = None,
filter_vessel_flags: Union[ID, List[ID]] = None,
filter_vessel_ice_class: Union[ID, List[ID]] = None,
filter_vessel_tags: Union[List[Tag], Tag] = None,
filter_vessel_risk_level: Union[str, List[str]] = None,
exclude_products: Union[ID, List[ID]] = None,
exclude_vessels: Union[ID, List[ID]] = None,
exclude_vessel_classes: Union[str, List[str]] = None,
exclude_vessel_status: str = None,
exclude_vessel_location: Union[ID, List[ID]] = None,
exclude_owners: Union[ID, List[ID]] = None,
exclude_effective_controllers: Union[ID, List[ID]] = None,
exclude_destination: Union[ID, List[ID]] = None,
exclude_filter_vessel_flags: Union[ID, List[ID]] = None,
exclude_filter_vessel_ice_class: Union[ID, List[ID]] = None,
exclude_filter_vessel_tags: Union[List[Tag], Tag] = None,
exclude_filter_vessel_risk_level: Union[str, List[str]] = None,
) -> TimeSeriesResult:
"""
Number and DWT of all vessels that can be available to load a given cargo at a given port,
grouped by the number of days to arrival.
# Arguments
filter_effective_controllers: An effective controller ID, or list of effective controller IDs to filter on.
filter_destination: A geography ID, or list of geography 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 'any_activity' for any other vessels
filter_vessel_location: A location ID, or list of location IDs to filter on.
filter_port: Filter by port ID.
filter_region: Filter by region ID - takes precedence over filter_port if provided. This should be used in conjunction with `use_reference_port`
filter_days_to_arrival: Filter availability by time to arrival in days`
use_reference_port: If this flag is enabled, we will return data for
the reference port instead of the user selected one,
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_idle_min: A number greater than 0 (representing idle days).
filter_vessel_idle_max: A number greater than 0 and filter_vessel_idle_min (representing idle days).
filter_vessel_dwt_min: A number between 0 and 550000.
filter_vessel_dwt_max: A number between 0 and 550000.
filter_vessel_scrubbers: Either inactive 'disabled', or included 'inc' or excluded 'exc'.
filter_vessel_flags: A flag ID, or list of flag IDs to filter on.
filter_vessel_ice_class: An ice class ID, or list of ice class IDs to filter on.
filter_vessel_tags: A tag ID, or list of tag IDs to filter on.
filter_vessel_risk_level: A risk level ID, or list of risk level IDs to filter on.
filter_recent_visits: Filter availability by each vessel's recent visits
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_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 'any_activity' for any other vessels
exclude_effective_controllers: An effective controller ID, or list of effective controller IDs to exclude.
exclude_vessel_location: A location ID, or list of location IDs to filter on.
exclude_destination: A location ID, or list of location IDs to filter on.
exclude_vessel_flags: A flag ID, or list of flag IDs to exclude.
exclude_vessel_ice_class: An ice class ID, or list of ice class IDs to exclude.
exclude_vessel_tags: A tag ID, or list of tag IDs to exclude.
exclude_vessel_risk_level: A risk level ID, or list of risk level IDs to exclude.
# Returns
`TimeSeriesResult`
# Example
_Breakdown of number and DWT of all vessels arriving at Rotterdam in the next 5 days._
```python
>>> from vortexasdk import VesselAvailabilityBreakdown, Geographies
>>> rotterdam = [g.id for g in Geographies().search("rotterdam").to_list() if "port" in g.layer]
>>> df = VesselAvailabilityBreakdown().search(
... filter_port=rotterdam[0],
... filter_days_to_arrival={"min": 0, "max": 5}
... ).to_df()
```
Gives the following:
| | key | value | count |
|---:|:-------------------------|----------:|----------:|
| 0 | 2021-06-23 00:00:00+00:00| 2939754 | 34 |
| 1 | 2021-06-24 00:00:00+00:00| 2676732 | 38 |
| 2 | 2021-06-25 00:00:00+00:00| 6262914 | 74 |
| 3 | 2021-06-26 00:00:00+00:00| 3445105 | 43 |
| 4 | 2021-06-27 00:00:00+00:00| 3924460 | 51 |
"""
exclude_params: Dict[str, Any] = {
"filter_destination": convert_to_list(exclude_destination),
"filter_products": convert_to_list(exclude_products),
"filter_vessels": convert_to_list(exclude_vessels),
"filter_vessel_classes": convert_to_list(exclude_vessel_classes),
"filter_owners": convert_to_list(exclude_owners),
"filter_effective_controllers": convert_to_list(
exclude_effective_controllers
),
"filter_vessel_status": convert_to_list(exclude_vessel_status),
"filter_vessel_location": convert_to_list(exclude_vessel_location),
"filter_vessel_flags": convert_to_list(
exclude_filter_vessel_flags
),
"filter_vessel_ice_class": convert_to_list(
exclude_filter_vessel_ice_class
),
"filter_vessel_tags": convert_to_list(exclude_filter_vessel_tags),
"filter_vessel_risk_level": convert_to_list(
exclude_filter_vessel_risk_level
),
}
api_params: Dict[str, Any] = {
"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_location": convert_to_list(filter_vessel_location),
"filter_owners": convert_to_list(filter_owners),
"filter_effective_controllers": convert_to_list(
filter_effective_controllers
),
"filter_destination": convert_to_list(filter_destination),
"filter_region": filter_region,
"filter_port": filter_port,
"use_reference_port": use_reference_port,
"filter_days_to_arrival": convert_to_list(filter_days_to_arrival),
"filter_vessel_dwt_min": filter_vessel_dwt_min,
"filter_vessel_dwt_max": filter_vessel_dwt_max,
"filter_vessel_age_min": filter_vessel_age_min,
"filter_vessel_age_max": filter_vessel_age_max,
"filter_vessel_idle_min": filter_vessel_idle_min,
"filter_vessel_idle_max": filter_vessel_idle_max,
"filter_vessel_scrubbers": filter_vessel_scrubbers,
"filter_recent_visits": filter_recent_visits,
"filter_vessel_flags": convert_to_list(filter_vessel_flags),
"filter_vessel_ice_class": convert_to_list(
filter_vessel_ice_class
),
"filter_vessel_tags": convert_to_list(filter_vessel_tags),
"filter_vessel_risk_level": convert_to_list(
filter_vessel_risk_level
),
"exclude": exclude_params,
}
response = super().search_with_client(
response_type="breakdown", **api_params
)
return TimeSeriesResult(
records=response["data"], reference=response["reference"]
)