varunayan.core module

class varunayan.core.ProcessingParams(request_id: str, variables: List[str], start_date: datetime.datetime, end_date: datetime.datetime, frequency: str = 'hourly', resolution: float = 0.25, dataset_type: str = 'single', pressure_levels: List[str] | None = None, north: float | None = None, south: float | None = None, east: float | None = None, west: float | None = None, geojson_file: str | None = None, geojson_data: Dict[str, Any] | None = None)

Bases: object

dataset_type: str = 'single'

east: float | None = None

end_date: datetime

frequency: str = 'hourly'

geojson_data: Dict[str, Any] | None = None

geojson_file: str | None = None

north: float | None = None

pressure_levels: List[str] | None = None

request_id: str

resolution: float = 0.25

south: float | None = None

start_date: datetime

variables: List[str]

west: float | None = None

varunayan.core.adjust_sum_variables(df: DataFrame, frequency: str) → None

Adjust sum variables based on temporal frequency

varunayan.core.aggregate_and_save(params: ProcessingParams, df: DataFrame, save_raw: bool)

Handle aggregation and saving of results

varunayan.core.calculate_map_dimensions(west: float, east: float, south: float, north: float) → Tuple[int, int]

Calculate proportional width/height for ASCII map

varunayan.core.cleanup_temp_files(request_id: str, temp_geojson_file: str)

Clean up temporary files

varunayan.core.download_with_retry(download_func: Callable[[...], str | None], params: ProcessingParams, chunk_id: str | None = None) → str | None

Generic download function with retry logic

varunayan.core.draw_geojson_ascii(geojson_data: Dict[str, Any])

Draws a mini ASCII map showing the GeoJSON polygons. :param geojson_data: Loaded GeoJSON data (must be FeatureCollection)

varunayan.core.era5ify_bbox(request_id: str, variables: List[str], start_date: str, end_date: str, north: float, south: float, east: float, west: float, dataset_type: str = 'single', pressure_levels: List[str] | None = None, frequency: str = 'hourly', resolution: float = 0.25, verbosity: int = 0, save_raw: bool = True) → DataFrame

Public function for processing with bounding box

varunayan.core.era5ify_geojson(request_id: str, variables: List[str], start_date: str, end_date: str, json_file: str, dataset_type: str = 'single', pressure_levels: List[str] | None = None, frequency: str = 'hourly', resolution: float = 0.25, verbosity: int = 0, save_raw: bool = True) → DataFrame

Public function for processing with GeoJSON

varunayan.core.era5ify_point(request_id: str, variables: List[str], start_date: str, end_date: str, latitude: float, longitude: float, dataset_type: str = 'single', pressure_levels: List[str] | None = None, frequency: str = 'hourly', verbosity: int = 0, save_raw: bool = True) → DataFrame

varunayan.core.load_and_validate_geojson(geojson_file: str) → Dict[str, Any]

Load and validate GeoJSON file

varunayan.core.parse_date(date_str: str) → datetime

Parse date string into datetime object

varunayan.core.print_bounding_box(params: ProcessingParams)

Print bounding box information

varunayan.core.print_processing_footer(params: ProcessingParams, result_df: DataFrame, total_start_time: float)

Print processing footer information

varunayan.core.print_processing_header(params: ProcessingParams)

Print processing header information

varunayan.core.print_processing_strategy(params: ProcessingParams)

Print processing strategy information

varunayan.core.process_era5(params: ProcessingParams, save_raw: bool)

Main entry point for ERA5 processing

varunayan.core.process_era5_data(params: ProcessingParams, chunk_info: Tuple[int, int] | None = None) → DataFrame | None

Core processing function for both single and pressure level data

varunayan.core.process_time_chunks(params: ProcessingParams, download_func: Callable[[...], str | None], process_func: Callable[[ProcessingParams, int | None, int | None], DataFrame | None]) → DataFrame | None

Handle time-based chunking of downloads and processing

varunayan.core.save_results(params: ProcessingParams, aggregated_df: DataFrame, unique_latlongs: DataFrame, raw_df: DataFrame, save_raw: bool)

Save all results to files

varunayan.core.set_verbosity(verbosity: int)

varunayan.core.validate_inputs(params: ProcessingParams)

Validate all input parameters