Speasy utils

speasy - an open source Python client for Space Physics web services such as CDAWEB or AMDA.

Functions

get_parameter_index

 get_parameter_index (param:str, ds:str)

get_dataset_parameters

 get_dataset_parameters (v:str, provider:str='cda')

get_dataset_index

 get_dataset_index (v:str, provider:str='cda')

get_provider

 get_provider (v:str)

SpeasyVariable.preview

 SpeasyVariable.preview ()

Data Classes

Based on SpeasyVariable class from speasy.

Variable

 Variable (name:str=None, description:str=None, unit:str=None,
           ts:datetime.timedelta=None,
           timerange:list[datetime.datetime]=None, dataset:str=None,
           parameter:str=None, product:str=None, **extra_data:Any)

*Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

A base class for creating Pydantic models.

Attributes: class_vars: The names of the class variables defined on the model. private_attributes: Metadata about the private attributes of the model. signature: The synthesized __init__ [Signature][inspect.Signature] of the model.

__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.
__pydantic_core_schema__: The core schema of the model.
__pydantic_custom_init__: Whether the model has a custom `__init__` function.
__pydantic_decorators__: Metadata containing the decorators defined on the model.
    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.
__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to
    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.
__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.
__pydantic_post_init__: The name of the post-init method for the model, if defined.
__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].
__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.
__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.

__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]
    is set to `'allow'`.
__pydantic_fields_set__: The names of fields explicitly set during instantiation.
__pydantic_private__: Values of private attributes set on the model instance.*

Variable.dump

 Variable.dump (path:str)

Dump the configuration to a file.

Variable.plot

 Variable.plot (fig=None, ax:matplotlib.axes._axes.Axes=None)

SVariables

 SVariables ()

Initialize self. See help(type(self)) for accurate signature.

Variables

 Variables (timerange:list[datetime.datetime]=None,
            variables:list[__main__.Variable]=None,
            parameters:list[str]=None, dataset:str=None,
            provider:str='cda', products:list[str|speasy.core.inventory.in
            dexes.ParameterIndex]=None)

*Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

A base class for creating Pydantic models.

Attributes: class_vars: The names of the class variables defined on the model. private_attributes: Metadata about the private attributes of the model. signature: The synthesized __init__ [Signature][inspect.Signature] of the model.

__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.
__pydantic_core_schema__: The core schema of the model.
__pydantic_custom_init__: Whether the model has a custom `__init__` function.
__pydantic_decorators__: Metadata containing the decorators defined on the model.
    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.
__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to
    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.
__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.
__pydantic_post_init__: The name of the post-init method for the model, if defined.
__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].
__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.
__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.

__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]
    is set to `'allow'`.
__pydantic_fields_set__: The names of fields explicitly set during instantiation.
__pydantic_private__: Values of private attributes set on the model instance.*
earth_start = "2019-04-09"
earth_end = "2019-04-12"
timerange = [earth_start, earth_end]

d = spz.get_data(
    get_parameter_index("MOM.P.MAGF", "WI_PLSP_3DP"),
    timerange,
)

Test

timerange = ["2019-04-07T01:00", "2019-04-07T12:00"]
vars = Variables(
    dataset="PSP_FLD_L2_MAG_RTN",
    parameters=["psp_fld_l2_mag_RTN"],
    timerange=timerange,
)
def data_provider_summary(data_provider: DataProvider = spz.cda):
    # show the name of the data_provider, the number of datasets, parameters and catalogs

    inventory = data_provider.flat_inventory
    print("Data Provider:", data_provider.provider_name)
    print("Datasets:", len(inventory.datasets))
    print("Parameters:", len(inventory.parameters))
    print("Catalogs:", len(inventory.catalogs))


# data_provider_summary(spz.cda)
# data_provider_summary(spz.amda)
# data_provider_summary(spz.csa)