Procedure Composite Process Instance – Django REST framework

Get a list of ProcedureComputation objects. ProcedureComputations have a 1:1 mapping with Observations where used.
These may have a number of 2 or more components made up of combinations of Computation and Acquisition records.
The details of the underlying records have been serialised.

### Available end points:

- `/ProcedureComputations/` - Will list all ProcedureComputations in the database
- `/ProcedureComputations.json` - Will return all ProcedureComputations in json format
- `/ProcedureComputations/<object_id>/` - Returns ProcedureComputations object with that id

### Available Methods:

- `GET`
- `HEAD`

### Available filters:

None
### How to use filters:

None

GET /api/v2/composites/45292/?format=api

HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "ob_id": 45292,
    "computationComponent": [
        {
            "ob_id": 45293,
            "uuid": "8a5d84c459c544189c12f7cb6d0fc0e5",
            "title": "Computation of ESA Precursors for Aerosols and Ozone Climate Change Initiative (Precursors_cci): monthly L3 HCHO from TROPOMI, version 2.0",
            "abstract": "The Formaldehyde(HCHO) Climate Data Record (CDR) product is a Level 3 HCHO product developed by using satellite data from the TROPOMI instrument (on S5P) as part of the ESA Climate Change Initiative (CCI) Precursors for Aerosols and Ozone project.\r\nThis dataset provides gridded HCHO tropospheric column densities of monthly 0.125°x0.125° resolution grids from May 2018 to December 2024.\r\n\r\nCompared to the operational TROPOMI product, the air mass factors have been reprocessed using an update albedo climatology, and the CAMS Reanalysis Model for the a priori vertical profiles. The background correction and the quality values have also been updated.\r\n\r\nIn addition to the main product results, such as HCHO slant column, vertical column and air mass factor, the Level 3 data files contain several additional parameters and diagnostic information such as uncertainties, a priori profiles and averaging kernels.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        }
    ],
    "acquisitionComponent": [
        {
            "ob_id": 45294,
            "independentInstrument": [],
            "instrumentplatformpair_set": [
                {
                    "ob_id": 14447,
                    "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/26439/?format=api",
                    "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/26444/?format=api",
                    "relatedTo": {
                        "ob_id": 45294,
                        "uuid": "dee9b03d75f841039aafa493073b3563",
                        "short_code": "acq"
                    }
                }
            ]
        }
    ],
    "identifier_set": [],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/216651/?format=api"
    ]
}