SmartOcean timeseries data model
The purpose of the data model is to support the exchange of time series data in particular exchange of fragments of data associated with time series delivered by the SFI Smart Ocean Platform: https://smartoceanplatform.github.io/
The data model is implemented based on the Pydantic framework: https://docs.pydantic.dev/latest/
Standards
The parameter and unit in the Observation class is to follow the Copernicus Marine in-situ TAC physical parameters list:
https://archimer.ifremer.fr/doc/00422/53381/
The qualityCodes is to follow the recommendations for in-situ data Near Real Time Quality Control:
https://archimer.ifremer.fr/doc/00251/36230/
The time object variable in the Datapoint class is to follow the ISO8601 standard and include timezone information.
Example of use
The code below provides an example of ow to use the classes of the library.
from sfisop.datamodels.tsdatamodel.timeseriesdata import *
a_location = Location(latitude=5.0, longitude=65)
meta_data = MetaData(description="test time series",
timeseries="timeseries_testdata",
origin="timeseries_testdata")
observation = Observation(source="test sensor",
source_id="test sensor id",
parameter="temperature",
value="5.0",
unit="celcius",
qualityCodes=[0])
data_point = DataPoint(dp_id="datapoint id",
source="test sensor hub",
source_id="test sensor hub id",
location=a_location,
time="2024-02-17T20:12:49.559547+01:00",
observations=[observation])
data_points = [data_point]
ts_data = TimeSeriesData(format="SMARTOCEAN_V1",
metadata=meta_data,
data=data_points)
The utility functions implemented in the tsdata_utils.py and timeseriesdata.py is to be used for serialisation and de-serialisation of time series data.
Further documentation can be found on the SFI Smart Ocean platform web pages: https://smartoceanplatform.github.io/interoperability/
Metadata
Release files for sfisop-datamodels 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| sfisop_datamodels-1.0.1.tar.gz | 3.4 kB | Without provenance | Details for sfisop_datamodels-1.0.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| sfisop_datamodels-1.0.1-py3-none-any.whl | Python 3 | none | any | Details for sfisop_datamodels-1.0.1-py3-none-any.whl |
Total release size: 8.1 kB
Release files / sfisop_datamodels-1.0.1.tar.gz
| Download URL | sfisop_datamodels-1.0.1.tar.gz |
|---|---|
| Size | 3.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
77347f03088e99384afbb252a40b4d4c76eecf5be476ecf78070b251b9720c21
|
|
BLAKE2b-256 checksum How to use checksums |
19ee94db776919903cf9317bf572c546efb9a65d8d6a03b02875dd79e19c9346
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.8.4 CPython/3.13.0 Darwin/24.2.0
|
Release files / sfisop_datamodels-1.0.1-py3-none-any.whl
| Download URL | sfisop_datamodels-1.0.1-py3-none-any.whl |
|---|---|
| Size | 4.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
6e1195fbb2e3b395d75c0fa677c389dac52a64dab861d73cdd455c690b66df9b
|
|
BLAKE2b-256 checksum How to use checksums |
84e6ff7e4f9ad1a9b9988a732ee1e4bcead3691f1ee1250b57d070711d2a61f0
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.8.4 CPython/3.13.0 Darwin/24.2.0
|
Security for sfisop-datamodels 1.0.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.