-
Notifications
You must be signed in to change notification settings - Fork 8
/
vessel_availability_breakdown.py
183 lines (137 loc) · 10.3 KB
/
vessel_availability_breakdown.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
"""
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 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.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_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,
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_destination: Union[ID, List[ID]] = 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_owners: An corporation ID, or list of corporation 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_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_owners: An owner ID, or list of owner 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.
# 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 = {
"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_vessel_status": convert_to_list(exclude_vessel_status),
"filter_vessel_location": convert_to_list(
exclude_vessel_location
),
}
api_params = {
"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_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,
"exclude": exclude_params,
}
return TimeSeriesResult(super().search(response_type="breakdown", **api_params))