Refactor if-else using match statements

Author: seisman

pygmt/src/x2sys_cross.py

@@ -197,26 +197,25 @@ def x2sys_cross(
 
     file_contexts = []
     for track in tracks:
-        kind = data_kind(track)
-        if kind == "file":
-            file_contexts.append(contextlib.nullcontext(track))
-        elif kind == "matrix":
-            # find suffix (-E) of trackfiles used (e.g. xyz, csv, etc) from
-            # $X2SYS_HOME/TAGNAME/TAGNAME.tag file
-            lastline = (
-                Path(os.environ["X2SYS_HOME"], kwargs["T"], f"{kwargs['T']}.tag")
-                .read_text(encoding="utf8")
-                .strip()
-                .split("\n")[-1]
-            )  # e.g. "-Dxyz -Etsv -I1/1"
-            for item in sorted(lastline.split()):  # sort list alphabetically
-                if item.startswith(("-E", "-D")):  # prefer -Etsv over -Dxyz
-                    suffix = item[2:]  # e.g. tsv (1st choice) or xyz (2nd choice)
-
-            # Save pandas.DataFrame track data to temporary file
-            file_contexts.append(tempfile_from_dftrack(track=track, suffix=suffix))
-        else:
-            raise GMTInvalidInput(f"Unrecognized data type: {type(track)}")
+        match data_kind(track):
+            case "file":
+                file_contexts.append(contextlib.nullcontext(track))
+            case "matrix":
+                # find suffix (-E) of trackfiles used (e.g. xyz, csv, etc) from
+                # $X2SYS_HOME/TAGNAME/TAGNAME.tag file
+                tagfile = Path(
+                    os.environ["X2SYS_HOME"], kwargs["T"], f"{kwargs['T']}.tag"
+                )
+                # Last line is like "-Dxyz -Etsv -I1/1"
+                lastline = tagfile.read_text().splitlines()[-1]
+                for item in sorted(lastline.split()):  # sort list alphabetically
+                    if item.startswith(("-E", "-D")):  # prefer -Etsv over -Dxyz
+                        suffix = item[2:]  # e.g. tsv (1st choice) or xyz (2nd choice)
+
+                # Save pandas.DataFrame track data to temporary file
+                file_contexts.append(tempfile_from_dftrack(track=track, suffix=suffix))
+            case _:
+                raise GMTInvalidInput(f"Unrecognized data type: {type(track)}")
 
     with Session() as lib:
         with lib.virtualfile_out(kind="dataset", fname=outfile) as vouttbl: