dapper.met.exporter¶
Meteorological data export pipelines.
Classes
|
Source-agnostic meteorological exporter. |
- class dapper.met.exporter.Exporter(adapter, src_path, *, domain, out_dir=None, calendar='noleap', dtime_resolution_hrs=1, dtime_units='days', dformat='BYPASS', append_attrs=None, chunks=None, include_vars=None, exclude_vars=None)[source]¶
Bases:
objectSource-agnostic meteorological exporter.
This class orchestrates a two-pass pipeline that ingests time-sharded CSVs for many sites/cells, preprocesses them via a pluggable adapter, and writes ELM-ready NetCDF outputs in two layouts:
"cellset"– one NetCDF per variable with dims('DTIME','lat','lon')(global packing; sparse lat/lon axes are OK)."sites"– one directory per site; each directory contains one NetCDF per variable with dims('n','DTIME')wheren=1(per-site packing).
Exporter is source-agnostic: all dataset-specific logic (file discovery, unit conversions, renaming to ELM short names, etc.) lives in an adapter that implements the BaseAdapter interface (e.g., an
ERA5Adapter). The exporter handles staging (CSV → per-site parquet), global DTIME axis creation, packing scans, chunking, and NetCDF I/O.- Parameters:
adapter (BaseAdapter) – Implements:
discover_files,normalize_locations,preprocess_shard,required_vars, andpack_params.csv_directory (str or pathlib.Path) – Directory containing time-sharded CSV files for all sites/cells.
out_dir (str or pathlib.Path) – Destination directory for NetCDF outputs and temporary parquet shards.
df_loc (pandas.DataFrame) – Locations table with at least columns
["gid","lat","lon"]; optional"zone". The adapter’snormalize_locations: - validates columns, - adds"lon_0-360", - fills/validates"zone", - sorts for stable site order.id_col (str, optional) – Kept for backward compatibility (unused when
"gid"is assumed).calendar ({"noleap","standard"}, default "noleap") – Calendar for numeric DTIME coordinate; Feb 29 filtered for “noleap”.
dtime_resolution_hrs (int, default 1) – Target time resolution in hours for the DTIME axis.
dtime_units ({"days","hours"}, default "days") – Units of the numeric DTIME coordinate (e.g.,
"days since YYYY-MM-DD HH:MM:SS").domain (Domain)
dformat (str)
append_attrs (dict | None)
- dformat{“BYPASS”,”DATM_MODE”}, default “BYPASS”
Target ELM format selector passed through to the adapter.
- append_attrsdict, optional
Extra global NetCDF attributes to include in every file. The exporter also adds:
export_mode("cellset"or"sites") andpack_scope("global"or"per-site").- chunkstuple[int,…], optional
Explicit NetCDF chunk sizes.
- include_vars / exclude_varsIterable[str], optional
Allow-/block-lists of ELM short names applied after preprocess. Meta columns
{"gid","time","LATIXY","LONGXY","zone"}are always kept.
Side Effects¶
Creates a temporary directory of per-site parquet shards under
out_dir.Writes NetCDF files to
out_dirin the chosen layout.Writes a
zone_mappings.txtfile either at the root (cellset) or inside each site directory (sites).
Notes
Packing: global packing for
cellset; per-site packing forsites.Required columns: CSV shards and
df_locboth use"gid"; CSVs include the adapter’s date/time column (renamed to"time"during preprocess).Combined (lat/lon) layout: does not enforce regular grids; axes are the unique sorted lat/lon from
df_loc(sparse OK).
- run(*, pack_scope=None, filename=None, overwrite=False)[source]¶
Run the MET export for this exporter’s Domain.
- The output layout is derived from
Domain.mode: sites: writes<run_dir>/<gid>/MET/{prefix_}{var}.ncand a per-sitezone_mappings.txt(always zone=01, id=1).cellset: writes<run_dir>/MET/{prefix_}{var}.ncand a singlezone_mappings.txtcovering all locations (zones taken from df_loc, default 1).
- Parameters:
pack_scope – Optional packing strategy override. Defaults to
per-sitefor sites andglobalfor cellset outputs.filename (
str|None) – Optional filename prefix for output NetCDF files. If provided, each variable is written to{filename}_{var}.nc.overwrite (
bool) – If True, clears existing MET outputs before writing.
- Return type:
None
- The output layout is derived from