/
vessel_availability_timeseries.py
252 lines (195 loc) · 13.5 KB
/
vessel_availability_timeseries.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
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
"""
Try me out in your browser:
[](https://mybinder.org/v2/gh/VorTECHsa/python-sdk/master?filepath=docs%2Fexamples%2Ftry_me_out%2Favailability_timeseries.ipynb)
"""
from typing import Any, List, Union, Dict
from vortexasdk.endpoints.timeseries_result import TimeSeriesResult
from vortexasdk.api.shared_types import to_ISODate
from vortexasdk.api import ID
from datetime import datetime
from vortexasdk.endpoints.endpoints import (
VESSEL_AVAILABILITY_TIMERSERIES_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 VesselAvailabilityTimeseries(Search):
"""
Please note: you will require a subscription to our Freight module to access this endpoint.
"""
def __init__(self):
Search.__init__(self, VESSEL_AVAILABILITY_TIMERSERIES_RESOURCE)
def search(
self,
filter_time_min: datetime = datetime(2019, 10, 1, 0),
filter_time_max: datetime = datetime(2019, 10, 1, 1),
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:
"""
Time series of the number of vessels that can be available to load a given cargo at a given port for
every day in the specified range.
# Arguments
filter_time_min: The UTC start date of the time filter.
filter_time_max: The UTC end date of the time filter.
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_recent_visits: Filter availability by each vessel's recent visits
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.
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
_Time series for the number of vessels available between 0 to 5 days, at port Rotterdam, over 4 days._
```python
>>> from vortexasdk import VesselAvailabilityTimeseries, Geographies
>>> from datetime import datetime
>>> rotterdam = "68faf65af1345067f11dc6723b8da32f00e304a6f33c000118fccd81947deb4e"
>>> start = datetime(2021, 6, 17)
>>> end = datetime(2021, 6, 21)
>>> df = (VesselAvailabilityTimeseries().search(
... filter_time_min=start,
... filter_time_max=end,
... filter_port=rotterdam,
... 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| 19225923 | 224 |
| 1 | 2021-06-24 00:00:00+00:00| 19634766 | 233 |
| 2 | 2021-06-25 00:00:00+00:00| 19154857 | 228 |
| 3 | 2021-06-26 00:00:00+00:00| 18410395 | 225 |
"""
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_time_min": to_ISODate(filter_time_min),
"filter_time_max": to_ISODate(filter_time_max),
"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"]
)