hydromt_wflow.components.WflowTablesComponent#

Summary of Methods and Attributes#

Component class	Methods	Attributes
`WflowTablesComponent`	`__init__()`, `close()`, `finish_write()`, `get_tables_merged()`, `read()`, `set()`, `test_equal()`, `write()`	`data`, `data_catalog`, `model`, `name_in_model`, `root`

class WflowTablesComponent(model: Model, filename: str = '{name}.csv')[source]#

Wflow specific tables component.

read(filename: str | None = None, **kwargs) → None[source]#: Read tables at provided or default file path if none is provided.

write(filename: str | None = None, **kwargs) → None[source]#: Write tables at provided or default file path if none is provided.

close() → None#: Clean up all open datasets. Method to be called before finish_write.

property data_catalog: DataCatalog#: Return the data catalog of the model this component is associated with.

finish_write()#

Finish the write functionality after cleanup was called for all components in the model.

All DeferredFileClose objects can overwrite any lazy loaded files now.

get_tables_merged() → DataFrame#: Return all tables of a model merged into one dataframe.

property model: Model#: Return the model object this component is associated with.

property name_in_model: str#: Find the name of the component in the parent model components.

property root: ModelRoot#: Return the root of the model this component is associated with.

set(tables: DataFrame | Series | Dict[str, DataFrame | Series], name: str | None = None) → None#

Add (a) table(s) <pandas.DataFrame> to model.

Parameters:

tables (pandas.DataFrame, pandas.Series or dict) – Table(s) to add to model. Multiple tables can be added at once by passing a dict of tables.
name (str, optional) – Name of table, by default None. Required when tables is not a dict.

Test if two components are equal.

Parameters:: other (ModelComponent) – The component to compare against.
Returns:: True if the components are equal, and a dict with the associated errors per property checked.
Return type:: tuple[bool, dict[str, str]]