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fix: use math.ceil() instead of int() for n_local_cores to prevent ZeroDivisionError on single-core machines #91

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fix: use math.ceil() instead of int() for n_local_cores to prevent ZeroDivisionError on single-core machines #91

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8d431a3
fix:use math.ceil() instead of int()
Mani212005 Feb 20, 2026
118fe5a
Merge branch 'main' into fix/math.ceil
joeloskarsson May 22, 2026
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6 changes: 4 additions & 2 deletions mllam_data_prep/cli.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
import argparse
import math
import os
from pathlib import Path

Expand Down Expand Up @@ -60,8 +61,9 @@ def call(args=None):
)
# get the number of system cores
n_system_cores = os.cpu_count()
# compute the number of cores to use
n_local_cores = int(args.dask_distributed_local_core_fraction * n_system_cores)
# compute the number of cores to use, using ceil to ensure at least 1
# worker is used even on single-core machines (e.g. standard GitHub CI)
n_local_cores = math.ceil(args.dask_distributed_local_core_fraction * n_system_cores)
# get the total system memory
total_memory = psutil.virtual_memory().total
# compute the memory per worker
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1 change: 1 addition & 0 deletions tests/test_distributed.py
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Expand Up @@ -28,6 +28,7 @@ def distributed():
"args",
[
["example.danra.yaml", "--dask-distributed-local-core-fraction", "1.0"],
["example.danra.yaml", "--dask-distributed-local-core-fraction", "0.5"],
["example.danra.yaml", "--dask-distributed-local-core-fraction", "0.0"],
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["example.danra.yaml"],
],
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