refine: Read a subset of metadata columns

Before these changes, all columns were read into memory even though only
the ID and date columns are used. This reads in just the two columns,
which brings performance improvements.

augur/refine.py

@@ -6,7 +6,7 @@
 from Bio import Phylo
 from .dates import get_numerical_dates
 from .dates.errors import InvalidYearBounds
-from .io.metadata import DEFAULT_DELIMITERS, DEFAULT_ID_COLUMNS, METADATA_DATE_COLUMN, InvalidDelimiter, read_metadata
+from .io.metadata import DEFAULT_DELIMITERS, DEFAULT_ID_COLUMNS, METADATA_DATE_COLUMN, InvalidDelimiter, Metadata, read_metadata
 from .utils import read_tree, write_json, InvalidTreeError
 from .errors import AugurError
 from treetime.vcf_utils import read_vcf
@@ -213,21 +213,24 @@ def run(args):
         if args.metadata is None:
             print("ERROR: meta data with dates is required for time tree reconstruction", file=sys.stderr)
             return 1
+
         try:
-            # TODO: load only the ID and date columns when read_metadata
-            # supports loading a subset of all columns.
-            metadata = read_metadata(
-                args.metadata,
-                delimiters=args.metadata_delimiters,
-                id_columns=args.metadata_id_columns,
-                dtype="string",
-            )
+            metadata_object = Metadata(args.metadata, args.metadata_delimiters, args.metadata_id_columns)
         except InvalidDelimiter:
             raise AugurError(
                 f"Could not determine the delimiter of {args.metadata!r}. "
                 f"Valid delimiters are: {args.metadata_delimiters!r}. "
                 "This can be changed with --metadata-delimiters."
             )
+
+        metadata = read_metadata(
+            args.metadata,
+            delimiters=[metadata_object.delimiter],
+            columns=[metadata_object.id_column, METADATA_DATE_COLUMN],
+            id_columns=[metadata_object.id_column],
+            dtype="string",
+        )
+
         try:
             dates = get_numerical_dates(metadata, fmt=args.date_format,
                                         min_max_year=args.year_bounds)