Module pyaurorax.search.ephemeris

Use the AuroraX search engine to search and upload ephemeris records.

Note that all functions and classes from submodules are all imported at this level of the ephemeris module. They can be referenced from here instead of digging in deeper to the submodules.

Sub-modules

pyaurorax.search.ephemeris.classes

Separated classes and functions used by the ephemeris module …

Classes

class EphemerisManager (aurorax_obj)

Expand source code

class EphemerisManager:
    """
    The EphemerisManager object is initialized within every PyAuroraX object. It acts as a way to access 
    the submodules and carry over configuration information in the super class.
    """

    __STANDARD_POLLING_SLEEP_TIME: float = 1.0  # polling sleep time when waiting for data (after the initial sleep time), in seconds
    __UPLOAD_CHUNK_SIZE = 500  # number of ephemeris records to upload at a time

    def __init__(self, aurorax_obj):
        self.__aurorax_obj = aurorax_obj

    def search(self,
               start: datetime.datetime,
               end: datetime.datetime,
               programs: Optional[List[str]] = None,
               platforms: Optional[List[str]] = None,
               instrument_types: Optional[List[str]] = None,
               metadata_filters: Optional[Union[MetadataFilter, List[Dict]]] = None,
               metadata_filters_logical_operator: Optional[Literal["and", "or", "AND", "OR"]] = None,
               response_format: Optional[Dict] = None,
               poll_interval: float = __STANDARD_POLLING_SLEEP_TIME,
               return_immediately: bool = False,
               verbose: bool = False) -> EphemerisSearch:
        """
        Search for ephemeris records

        By default, this function will block and wait until the request completes and
        all data is downloaded. If you don't want to wait, set the 'return_immediately`
        value to True. The Search object will be returned right after the search has been
        started, and you can use the helper functions as part of that object to get the
        data when it's done.

        Note: At least one search criteria from programs, platforms, or
        instrument_types, must be specified.

        Args:
            start (datetime.datetime): 
                Start timestamp of the search (inclusive)

            end (datetime.datetime): 
                End timestamp of the search (inclusive)

            programs (List[str]): 
                List of programs to search through, defaults to None

            platforms (List[str]): 
                List of platforms to search through, defaults to None

            instrument_types (List[str]): 
                List of instrument types to search through, defaults to None

            metadata_filters (MetadataFilter or List[Dict]): 
                The metadata filters to use when searching, defaults to None

            metadata_filters_logical_operator (str): 
                The logical operator to use when evaluating metadata filters (either `and` or `or`), 
                defaults to `and`. This parameter is deprecated in exchange for passing a 
                MetadataFilter object into the metadata_filters parameter. 

            response_format (Dict): 
                JSON representation of desired data response format

            poll_interval (float): 
                Time in seconds to wait between polling attempts, defaults to 1 second

            return_immediately (bool): 
                Initiate the search and return without waiting for data to be received, defaults to False

            verbose (bool): 
                Output poll times and other progress messages, defaults to False

        Returns:
            A `pyaurorax..search.EphemerisSearch` object

        Raises:
            pyaurorax.exceptions.AuroraXAPIError: An API error was encountered
        """
        # return
        return func_search(
            self.__aurorax_obj,
            start,
            end,
            programs,
            platforms,
            instrument_types,
            metadata_filters,
            metadata_filters_logical_operator,
            response_format,
            poll_interval,
            return_immediately,
            verbose,
        )

    def upload(self, identifier: int, records: List[EphemerisData], validate_source: bool = False, chunk_size: int = __UPLOAD_CHUNK_SIZE) -> int:
        """
        Upload ephemeris records to AuroraX

        Args:
            identifier (int): 
                AuroraX data source ID

            records (List[EphemerisData]): 
                Ephemeris records to upload

            validate_source (bool): 
                Validate all records before uploading, defaults to False

            chunk_size (int): 
                Number of records to upload in a single call, defaults to 500

        Returns:
            0 for success, raises exception on error

        Raises:
            pyaurorax.exceptions.AuroraXUploadError: Upload error
            pyaurorax.exceptions.AuroraXAPIError: An API error was encountered
        """
        return func_upload(self.__aurorax_obj, identifier, records, validate_source, chunk_size)

    def delete(self, data_source: DataSource, start: datetime.datetime, end: datetime.datetime) -> int:
        """
        Delete ephemeris records between a timeframe.

        The API processes this request asynchronously, so this method will return
        immediately whether or not the data has already been deleted.

        Args:
            data_source (DataSource): 
                Data source associated with the data product records (note that
                identifier, program, platform, and instrument_type are required)

            start (datetime.datetime): 
                Timestamp marking beginning of range to delete records for, inclusive
            
            end (datetime.datetime): 
                Timestamp marking end of range to delete records for, inclusive

        Returns:
            0 on success

        Raises:
            pyaurorax.exceptions.AuroraXNotFoundError: Source not found
            pyaurorax.exceptions.AuroraXUnauthorizedError: Invalid API key for this operation
            pyaurorax.exceptions.AuroraXAPIError: An API error was encountered
        """
        return func_delete(self.__aurorax_obj, data_source, start, end)

    def describe(self, search_obj: Optional[EphemerisSearch] = None, query_dict: Optional[Dict] = None) -> str:
        """
        Describe an ephemeris search as an "SQL-like" string. Either a EphemerisSearch
        object can be supplied, or a dictionary of the raw JSON query.

        Args:
            search_obj (EphemerisSearch): 
                The ephemeris search to describe, optional

            query_dict (Dict): 
                The ephemeris search query represented as a raw dictionary, optional

        Returns:
            The "SQL-like" string describing the ephemeris search object
        """
        return func_describe(self.__aurorax_obj, search_obj, query_dict)

    def get_request_url(self, request_id: str) -> str:
        """
        Get the ephemeris search request URL for a given request ID. This URL can be 
        used for subsequent pyaurorax.requests function calls. Primarily this method 
        facilitates delving into details about a set of already-submitted ephemeris 
        searches.

        Args:
            request_id (str): 
                The request identifier

        Returns:
            The request URL
        """
        return func_get_request_url(self.__aurorax_obj, request_id)

    def create_response_format_template(self, default: bool = True) -> Dict:
        """
        Generate a template dictionary that can be used as the response_format parameter
        in an ephemeris search.

        Args:
            default (bool): 
                The default value to set for every parameter that can be returned, defaults
                to True.

        Returns:
            A template dictionary for the response format
        """
        return {
            "data_source": {
                "identifier": default,
                "program": default,
                "platform": default,
                "instrument_type": default,
                "source_type": default,
                "display_name": default,
                "ephemeris_metadata_schema": {
                    "field_name": default,
                    "description": default,
                    "data_type": default,
                    "allowed_values": default,
                    "additional_description": default
                },
                "data_product_metadata_schema": {
                    "field_name": default,
                    "description": default,
                    "data_type": default,
                    "allowed_values": default,
                    "additional_description": default
                },
                "owner": default,
                "maintainers": default,
                "metadata": default
            },
            "epoch": default,
            "location_geo": {
                "lat": default,
                "lon": default
            },
            "location_gsm": {
                "lat": default,
                "lon": default
            },
            "nbtrace": {
                "lat": default,
                "lon": default
            },
            "sbtrace": {
                "lat": default,
                "lon": default
            },
            "metadata": default
        }

The EphemerisManager object is initialized within every PyAuroraX object. It acts as a way to access the submodules and carry over configuration information in the super class.

Methods

def create_response_format_template(self, default: bool = True) ‑> Dict

Expand source code

def create_response_format_template(self, default: bool = True) -> Dict:
    """
    Generate a template dictionary that can be used as the response_format parameter
    in an ephemeris search.

    Args:
        default (bool): 
            The default value to set for every parameter that can be returned, defaults
            to True.

    Returns:
        A template dictionary for the response format
    """
    return {
        "data_source": {
            "identifier": default,
            "program": default,
            "platform": default,
            "instrument_type": default,
            "source_type": default,
            "display_name": default,
            "ephemeris_metadata_schema": {
                "field_name": default,
                "description": default,
                "data_type": default,
                "allowed_values": default,
                "additional_description": default
            },
            "data_product_metadata_schema": {
                "field_name": default,
                "description": default,
                "data_type": default,
                "allowed_values": default,
                "additional_description": default
            },
            "owner": default,
            "maintainers": default,
            "metadata": default
        },
        "epoch": default,
        "location_geo": {
            "lat": default,
            "lon": default
        },
        "location_gsm": {
            "lat": default,
            "lon": default
        },
        "nbtrace": {
            "lat": default,
            "lon": default
        },
        "sbtrace": {
            "lat": default,
            "lon": default
        },
        "metadata": default
    }

Generate a template dictionary that can be used as the response_format parameter in an ephemeris search.

Args

default : bool

The default value to set for every parameter that can be returned, defaults to True.

Returns

A template dictionary for the response format

def delete(self,
data_source: DataSource,
start: datetime.datetime,
end: datetime.datetime) ‑> int

Expand source code

def delete(self, data_source: DataSource, start: datetime.datetime, end: datetime.datetime) -> int:
    """
    Delete ephemeris records between a timeframe.

    The API processes this request asynchronously, so this method will return
    immediately whether or not the data has already been deleted.

    Args:
        data_source (DataSource): 
            Data source associated with the data product records (note that
            identifier, program, platform, and instrument_type are required)

        start (datetime.datetime): 
            Timestamp marking beginning of range to delete records for, inclusive
        
        end (datetime.datetime): 
            Timestamp marking end of range to delete records for, inclusive

    Returns:
        0 on success

    Raises:
        pyaurorax.exceptions.AuroraXNotFoundError: Source not found
        pyaurorax.exceptions.AuroraXUnauthorizedError: Invalid API key for this operation
        pyaurorax.exceptions.AuroraXAPIError: An API error was encountered
    """
    return func_delete(self.__aurorax_obj, data_source, start, end)

Delete ephemeris records between a timeframe.

The API processes this request asynchronously, so this method will return immediately whether or not the data has already been deleted.

Args

data_source : DataSource

Data source associated with the data product records (note that identifier, program, platform, and instrument_type are required)

start : datetime.datetime

Timestamp marking beginning of range to delete records for, inclusive

end : datetime.datetime

Timestamp marking end of range to delete records for, inclusive

Returns

0 on success

Raises

AuroraXNotFoundError

Source not found

AuroraXUnauthorizedError

Invalid API key for this operation

AuroraXAPIError

An API error was encountered

def describe(self,
search_obj: EphemerisSearch | None = None,
query_dict: Dict | None = None) ‑> str

Expand source code

def describe(self, search_obj: Optional[EphemerisSearch] = None, query_dict: Optional[Dict] = None) -> str:
    """
    Describe an ephemeris search as an "SQL-like" string. Either a EphemerisSearch
    object can be supplied, or a dictionary of the raw JSON query.

    Args:
        search_obj (EphemerisSearch): 
            The ephemeris search to describe, optional

        query_dict (Dict): 
            The ephemeris search query represented as a raw dictionary, optional

    Returns:
        The "SQL-like" string describing the ephemeris search object
    """
    return func_describe(self.__aurorax_obj, search_obj, query_dict)

Describe an ephemeris search as an "SQL-like" string. Either a EphemerisSearch object can be supplied, or a dictionary of the raw JSON query.

Args

search_obj : EphemerisSearch

The ephemeris search to describe, optional

query_dict : Dict

The ephemeris search query represented as a raw dictionary, optional

Returns

The "SQL-like" string describing the ephemeris search object

def get_request_url(self, request_id: str) ‑> str

Expand source code

def get_request_url(self, request_id: str) -> str:
    """
    Get the ephemeris search request URL for a given request ID. This URL can be 
    used for subsequent pyaurorax.requests function calls. Primarily this method 
    facilitates delving into details about a set of already-submitted ephemeris 
    searches.

    Args:
        request_id (str): 
            The request identifier

    Returns:
        The request URL
    """
    return func_get_request_url(self.__aurorax_obj, request_id)

Get the ephemeris search request URL for a given request ID. This URL can be used for subsequent pyaurorax.requests function calls. Primarily this method facilitates delving into details about a set of already-submitted ephemeris searches.

Args

request_id : str

The request identifier

Returns

The request URL

def search(self,
start: datetime.datetime,
end: datetime.datetime,
programs: List[str] | None = None,
platforms: List[str] | None = None,
instrument_types: List[str] | None = None,
metadata_filters: MetadataFilter | List[Dict] | None = None,
metadata_filters_logical_operator: Literal['and', 'or', 'AND', 'OR'] | None = None,
response_format: Dict | None = None,
poll_interval: float = 1.0,
return_immediately: bool = False,
verbose: bool = False) ‑> EphemerisSearch

Expand source code

def search(self,
           start: datetime.datetime,
           end: datetime.datetime,
           programs: Optional[List[str]] = None,
           platforms: Optional[List[str]] = None,
           instrument_types: Optional[List[str]] = None,
           metadata_filters: Optional[Union[MetadataFilter, List[Dict]]] = None,
           metadata_filters_logical_operator: Optional[Literal["and", "or", "AND", "OR"]] = None,
           response_format: Optional[Dict] = None,
           poll_interval: float = __STANDARD_POLLING_SLEEP_TIME,
           return_immediately: bool = False,
           verbose: bool = False) -> EphemerisSearch:
    """
    Search for ephemeris records

    By default, this function will block and wait until the request completes and
    all data is downloaded. If you don't want to wait, set the 'return_immediately`
    value to True. The Search object will be returned right after the search has been
    started, and you can use the helper functions as part of that object to get the
    data when it's done.

    Note: At least one search criteria from programs, platforms, or
    instrument_types, must be specified.

    Args:
        start (datetime.datetime): 
            Start timestamp of the search (inclusive)

        end (datetime.datetime): 
            End timestamp of the search (inclusive)

        programs (List[str]): 
            List of programs to search through, defaults to None

        platforms (List[str]): 
            List of platforms to search through, defaults to None

        instrument_types (List[str]): 
            List of instrument types to search through, defaults to None

        metadata_filters (MetadataFilter or List[Dict]): 
            The metadata filters to use when searching, defaults to None

        metadata_filters_logical_operator (str): 
            The logical operator to use when evaluating metadata filters (either `and` or `or`), 
            defaults to `and`. This parameter is deprecated in exchange for passing a 
            MetadataFilter object into the metadata_filters parameter. 

        response_format (Dict): 
            JSON representation of desired data response format

        poll_interval (float): 
            Time in seconds to wait between polling attempts, defaults to 1 second

        return_immediately (bool): 
            Initiate the search and return without waiting for data to be received, defaults to False

        verbose (bool): 
            Output poll times and other progress messages, defaults to False

    Returns:
        A `pyaurorax..search.EphemerisSearch` object

    Raises:
        pyaurorax.exceptions.AuroraXAPIError: An API error was encountered
    """
    # return
    return func_search(
        self.__aurorax_obj,
        start,
        end,
        programs,
        platforms,
        instrument_types,
        metadata_filters,
        metadata_filters_logical_operator,
        response_format,
        poll_interval,
        return_immediately,
        verbose,
    )

Search for ephemeris records

By default, this function will block and wait until the request completes and all data is downloaded. If you don't want to wait, set the 'return_immediately` value to True. The Search object will be returned right after the search has been started, and you can use the helper functions as part of that object to get the data when it's done.

Note: At least one search criteria from programs, platforms, or instrument_types, must be specified.

Args

start : datetime.datetime

Start timestamp of the search (inclusive)

end : datetime.datetime

End timestamp of the search (inclusive)

programs : List[str]

List of programs to search through, defaults to None

platforms : List[str]

List of platforms to search through, defaults to None

instrument_types : List[str]

List of instrument types to search through, defaults to None

metadata_filters : MetadataFilter or List[Dict]

The metadata filters to use when searching, defaults to None

metadata_filters_logical_operator : str

The logical operator to use when evaluating metadata filters (either and or or), defaults to and. This parameter is deprecated in exchange for passing a MetadataFilter object into the metadata_filters parameter.

response_format : Dict

JSON representation of desired data response format

poll_interval : float

Time in seconds to wait between polling attempts, defaults to 1 second

return_immediately : bool

Initiate the search and return without waiting for data to be received, defaults to False

verbose : bool

Output poll times and other progress messages, defaults to False

Returns

A pyaurorax..search.EphemerisSearch object

Raises

AuroraXAPIError

An API error was encountered

def upload(self,
identifier: int,
records: List[EphemerisData],
validate_source: bool = False,
chunk_size: int = 500) ‑> int

Expand source code

def upload(self, identifier: int, records: List[EphemerisData], validate_source: bool = False, chunk_size: int = __UPLOAD_CHUNK_SIZE) -> int:
    """
    Upload ephemeris records to AuroraX

    Args:
        identifier (int): 
            AuroraX data source ID

        records (List[EphemerisData]): 
            Ephemeris records to upload

        validate_source (bool): 
            Validate all records before uploading, defaults to False

        chunk_size (int): 
            Number of records to upload in a single call, defaults to 500

    Returns:
        0 for success, raises exception on error

    Raises:
        pyaurorax.exceptions.AuroraXUploadError: Upload error
        pyaurorax.exceptions.AuroraXAPIError: An API error was encountered
    """
    return func_upload(self.__aurorax_obj, identifier, records, validate_source, chunk_size)

Upload ephemeris records to AuroraX

Args

identifier : int

AuroraX data source ID

records : List[EphemerisData]

Ephemeris records to upload

validate_source : bool

Validate all records before uploading, defaults to False

chunk_size : int

Number of records to upload in a single call, defaults to 500

Returns

0 for success, raises exception on error

Raises

AuroraXUploadError

Upload error

AuroraXAPIError

An API error was encountered