chunk delayed export to limit the number of files

src/qcodes/dataset/data_set.py

@@ -14,7 +14,7 @@
 from typing import TYPE_CHECKING, Any, Literal
 
 import numpy
-from tqdm.auto import trange
+from tqdm.auto import tqdm
 
 import qcodes
 from qcodes.dataset.data_set_protocol import (
@@ -246,7 +246,8 @@ def __init__(
         #: In memory representation of the data in the dataset.
         self._cache: DataSetCacheWithDBBackend = DataSetCacheWithDBBackend(self)
         self._results: list[dict[str, VALUE]] = []
-        self._in_memory_cache = in_memory_cache
+        self._in_memory_cache: bool = in_memory_cache
+        self._max_num_files_export = 100
         self._export_limit = 1000
 
         if run_id is not None:
@@ -1484,6 +1485,21 @@ def _set_export_info(self, export_info: ExportInfo) -> None:
 
     def _export_as_netcdf(self, path: Path, file_name: str) -> Path:
         """Export data as netcdf to a given path with file prefix"""
+
+        def generate_steps(num_rows, max_num_steps) -> list[tuple[int, int]]:
+            if max_num_steps >= num_rows:
+                return [(i + 1, i + 1) for i in range(num_rows)]
+
+            step_size, remainder = divmod(num_rows, max_num_steps)
+            limits = [
+                (i * step_size + 1, (i + 1) * step_size) for i in range(max_num_steps)
+            ]
+
+            if remainder > 0:
+                limits[-1] = (limits[-1][0], (step_size) * max_num_steps + remainder)
+
+            return limits
+
         import xarray as xr
 
         file_path = path / file_name
@@ -1514,12 +1530,16 @@ def _export_as_netcdf(self, path: Path, file_name: str) -> Path:
                         "temp_dir": temp_dir,
                     },
                 )
-                num_files = len(self)
+                num_rows = len(self)
+                steps = generate_steps(num_rows, self._max_num_files_export)
+                num_files = len(steps)
                 num_digits = len(str(num_files))
                 file_name_template = f"ds_{{:0{num_digits}d}}.nc"
-                for i in trange(num_files, desc="Writing individual files"):
+                for i, (start, stop) in tqdm(
+                    enumerate(steps), total=num_files, desc="Writing individual files"
+                ):
                     xarray_to_h5netcdf_with_complex_numbers(
-                        self.to_xarray_dataset(start=i + 1, end=i + 1),
+                        self.to_xarray_dataset(start=start, end=stop),
                         temp_path / file_name_template.format(i),
                     )
                 files = tuple(temp_path.glob("*.nc"))