pygmt.select: Improve performance by storing output in virtual files

pygmt/src/select.py

@@ -2,14 +2,17 @@
 select - Select data table subsets based on multiple spatial criteria.
 """
 
+from typing import Literal
+
+import numpy as np
 import pandas as pd
 from pygmt.clib import Session
 from pygmt.helpers import (
-    GMTTempFile,
     build_arg_string,
     fmt_docstring,
     kwargs_to_strings,
     use_alias,
+    validate_output_table_type,
 )
 
 __doctest_skip__ = ["select"]
@@ -41,7 +44,12 @@
     w="wrap",
 )
 @kwargs_to_strings(M="sequence", R="sequence", i="sequence_comma", o="sequence_comma")
-def select(data=None, outfile=None, **kwargs):
+def select(
+    data=None,
+    output_type: Literal["pandas", "numpy", "file"] = "pandas",
+    outfile: str | None = None,
+    **kwargs,
+) -> pd.DataFrame | np.ndarray | None:
     r"""
     Select data table subsets based on multiple spatial criteria.
 
@@ -70,8 +78,8 @@ def select(data=None, outfile=None, **kwargs):
     data : str, {table-like}
         Pass in either a file name to an ASCII data table, a 2-D
         {table-classes}.
-    outfile : str
-        The file name for the output ASCII file.
+    {output_type}
+    {outfile}
     {area_thresh}
     dist2pt : str
         *pointfile*\|\ *lon*/*lat*\ **+d**\ *dist*.
@@ -180,12 +188,12 @@ def select(data=None, outfile=None, **kwargs):
 
     Returns
     -------
-    output : pandas.DataFrame or None
-        Return type depends on whether the ``outfile`` parameter is set:
+    ret
+        Return type depends on ``outfile`` and ``output_type``:
 
-        - :class:`pandas.DataFrame` table if ``outfile`` is not set.
-        - None if ``outfile`` is set (filtered output will be stored in file
-          set by ``outfile``).
+        - None if ``outfile`` is set (output will be stored in file set by ``outfile``)
+        - :class:`pandas.DataFrame` or :class:`numpy.ndarray` if ``outfile`` is not set
+          (depends on ``output_type``)
 
     Example
     -------
@@ -196,25 +204,23 @@ def select(data=None, outfile=None, **kwargs):
     >>> # longitudes 246 and 247 and latitudes 20 and 21
     >>> out = pygmt.select(data=ship_data, region=[246, 247, 20, 21])
     """
-
-    with GMTTempFile(suffix=".csv") as tmpfile:
-        with Session() as lib:
-            with lib.virtualfile_in(check_kind="vector", data=data) as vintbl:
-                if outfile is None:
-                    outfile = tmpfile.name
-                lib.call_module(
-                    module="select",
-                    args=build_arg_string(kwargs, infile=vintbl, outfile=outfile),
-                )
-
-        # Read temporary csv output to a pandas table
-        if outfile == tmpfile.name:  # if user did not set outfile, return pd.DataFrame
-            try:
-                column_names = data.columns.to_list()
-                result = pd.read_csv(tmpfile.name, sep="\t", names=column_names)
-            except AttributeError:  # 'str' object has no attribute 'columns'
-                result = pd.read_csv(tmpfile.name, sep="\t", header=None, comment=">")
-        elif outfile != tmpfile.name:  # return None if outfile set, output in outfile
-            result = None
-
-    return result
+    output_type = validate_output_table_type(output_type, outfile=outfile)
+
+    column_names = None
+    if output_type == "pandas" and isinstance(data, pd.DataFrame):
+        column_names = data.columns.to_list()
+
+    with Session() as lib:
+        with (
+            lib.virtualfile_in(check_kind="vector", data=data) as vintbl,
+            lib.virtualfile_out(kind="dataset", fname=outfile) as vouttbl,
+        ):
+            lib.call_module(
+                module="select",
+                args=build_arg_string(kwargs, infile=vintbl, outfile=vouttbl),
+            )
+        return lib.virtualfile_to_dataset(
+            output_type=output_type,
+            vfile=vouttbl,
+            column_names=column_names,
+        )