floodresilience.tasks

Runs backend tasks using Celery. Allowing for multiple long-running tasks to complete in the background. Allows the frontend to send tasks and retrieve status later.

Attributes

log

Classes

DepthTimePlot

Represents the depths over time for a particular pixel location in a raster.

Functions

`on_startup`(→ None)	Initialise database, runs when Celery instance is ready.
`create_model_for_area`(→ celery.result.GroupResult)	Create a model for the area using series of chained (sequential) sub-tasks.
`process_dem`(→ None)	Task to ensure hydrologically-conditioned DEM is processed for the given area and added to the database.
`generate_rainfall_inputs`(→ None)	Task to ensure rainfall input data for the given area is added to the database and model input files are created.
`generate_tide_inputs`(→ None)	Task to ensure tide input data for the given area is added to the database and model input files are created.
`generate_river_inputs`(→ None)	Task to ensure river input data for the given area is added to the database and model input files are created.
`run_flood_model`(→ int)	Task to run flood model using input data from previous tasks.
`refresh_lidar_datasets`(→ None)	Web-scrapes OpenTopography metadata to create the datasets table containing links to LiDAR data sources.
`ensure_lidar_datasets_initialised`(→ None)	Check if LiDAR datasets table is initialised.
`get_model_output_filepath_from_model_id`(→ str)	Task to query the database and find the filepath for the model output for the model_id.
`get_depth_by_time_at_point`(→ DepthTimePlot)	Task to query a point in a flood model output and return the list of depths and times.
`get_model_extents_bbox`(→ str)	Task to find the bounding box of a given model output.
`get_valid_parameters_based_on_confidence_level`(...)	Task to get information on valid tide and sea-level-rise parameters based on the valid values in the database.
`validate_slr_parameters`(...)	Task to validate each of the sea-level-rise parameters.

Module Contents

floodresilience.tasks.log

class floodresilience.tasks.DepthTimePlot

Bases: NamedTuple

Represents the depths over time for a particular pixel location in a raster. Uses tuples and lists instead of Arrays or Dataframes because it needs to be easily serializable when communicating over message_broker.

depths

A list of all of the depths in m for the pixel. Parallels the times list

Type:: List[float]

times

A list of all of the times in s for the pixel. Parallels the depts list

Type:: List[float]

depths: List[float]

times: List[float]

floodresilience.tasks.on_startup(sender: celery.worker.consumer.Consumer, **_kwargs: None) → None

Initialise database, runs when Celery instance is ready.

Parameters:: sender (Consumer) – The Celery worker node instance

floodresilience.tasks.create_model_for_area(selected_polygon_wkt: str, scenario_options: dict) → celery.result.GroupResult

Create a model for the area using series of chained (sequential) sub-tasks.

Parameters:

selected_polygon_wkt (str) – The polygon defining the selected area to run the model for. Defined in WKT form.
scenario_options (dict) – Options for scenario modelling inputs.

Returns:

The task result for the long-running group of tasks. The task ID represents the final task in the group.

Return type:

result.GroupResult

floodresilience.tasks.process_dem(selected_polygon_wkt: str) → None

Task to ensure hydrologically-conditioned DEM is processed for the given area and added to the database.

Parameters:: selected_polygon_wkt (str) – The polygon defining the selected area to process the DEM for. Defined in WKT form.

floodresilience.tasks.generate_rainfall_inputs(selected_polygon_wkt: str) → None

Task to ensure rainfall input data for the given area is added to the database and model input files are created.

Parameters:: selected_polygon_wkt (str) – The polygon defining the selected area to add rainfall data for. Defined in WKT form.

floodresilience.tasks.generate_tide_inputs(selected_polygon_wkt: str, scenario_options: dict) → None

Task to ensure tide input data for the given area is added to the database and model input files are created.

Parameters:

selected_polygon_wkt (str) – The polygon defining the selected area to add tide data for. Defined in WKT form.
scenario_options (dict) – Options for scenario modelling inputs.

floodresilience.tasks.generate_river_inputs(selected_polygon_wkt: str) → None

Task to ensure river input data for the given area is added to the database and model input files are created.

Parameters:: selected_polygon_wkt (str) – The polygon defining the selected area to add river data for. Defined in WKT form.

floodresilience.tasks.run_flood_model(selected_polygon_wkt: str) → int

Task to run flood model using input data from previous tasks.

Parameters:: selected_polygon_wkt (str) – The polygon defining the selected area to run the flood model for. Defined in WKT form.
Returns:: The database ID of the flood model that has been run.
Return type:: int

floodresilience.tasks.refresh_lidar_datasets() → None: Web-scrapes OpenTopography metadata to create the datasets table containing links to LiDAR data sources. Takes a long time to run but needs to be run periodically so that the datasets are up to date.

floodresilience.tasks.ensure_lidar_datasets_initialised() → None: Check if LiDAR datasets table is initialised. This table holds URLs to data sources for LiDAR. If it is not initialised, then it initialises it by web-scraping OpenTopography which takes a long time.

floodresilience.tasks.get_model_output_filepath_from_model_id(model_id: int) → str

Task to query the database and find the filepath for the model output for the model_id.

Parameters:: model_id (int) – The database id of the model output to query.
Returns:: Serialized posix-style str version of the filepath.
Return type:: str

floodresilience.tasks.get_depth_by_time_at_point(model_id: int, lat: float, lng: float) → DepthTimePlot

Task to query a point in a flood model output and return the list of depths and times.

Parameters:

model_id (int) – The database id of the model output to query.
lat (float) – The latitude of the point to query.
lng (float) – The longitude of the point to query.

Returns:

Tuple of depths list and times list for the pixel in the output nearest to the point.

Return type:

DepthTimePlot

floodresilience.tasks.get_model_extents_bbox(model_id: int) → str

Task to find the bounding box of a given model output.

Parameters:: model_id (int) – The database id of the model output to query.
Returns:: The bounding box in ‘x1,y1,x2,y2’ format.
Return type:: str

floodresilience.tasks.get_valid_parameters_based_on_confidence_level() → Dict[str, Dict[str, str | int]]

Task to get information on valid tide and sea-level-rise parameters based on the valid values in the database. These parameters are mostly dependent on the “confidence_level” parameter, so that is the key in the returned dict.

Returns:: Dictionary with confidence_level as the key, and 2nd level dict with allowed values for dependent values.
Return type:: Dict[str, Dict[str, Union[str, int]]]

floodresilience.tasks.validate_slr_parameters(scenario_options: Dict[str, str | float | int | bool]) → floodresilience.dynamic_boundary_conditions.tide.main_tide_slr.ValidationResult

Task to validate each of the sea-level-rise parameters.

Parameters:: scenario_options (Dict[str, Union[str, float, int, bool]]) – Options for scenario modelling inputs, coming from JSON body.
Returns:: Result of the validation, with validation failure reason if applicable
Return type:: main_tide_slr.ValidationResult