From fa2d30b58aeccef05e3780581f1101ec3264b704 Mon Sep 17 00:00:00 2001
From: Marnix <marnix.kraus@deltares.nl>
Date: Mon, 16 Dec 2024 16:56:50 +0100
Subject: [PATCH 01/12] Test that shows jinja can use generator functions

To keep the load small, we need to write files via generators,
not simply via one big string.
Using file.writelines() is buffered, and the dask array is buffered.
---
 flopy4/xarray_jinja/filters.py                | 12 ++++++++
 .../templates/disu_template.disu.jinja        |  5 ++++
 test/test_xarray_jinja.py                     | 28 +++++++++++++++++++
 3 files changed, 45 insertions(+)
 create mode 100644 flopy4/xarray_jinja/filters.py
 create mode 100644 flopy4/xarray_jinja/templates/disu_template.disu.jinja
 create mode 100644 test/test_xarray_jinja.py

diff --git a/flopy4/xarray_jinja/filters.py b/flopy4/xarray_jinja/filters.py
new file mode 100644
index 0000000..08e0e75
--- /dev/null
+++ b/flopy4/xarray_jinja/filters.py
@@ -0,0 +1,12 @@
+import numpy as np
+import xarray as xr
+
+
+def dask_expand(data: xr.DataArray):
+    for block in data.data.blocks:
+        block_data = block.compute()
+        yield block_data
+
+
+def nparray2string(data: np.ndarray):
+    return " ".join(data.astype(str))
diff --git a/flopy4/xarray_jinja/templates/disu_template.disu.jinja b/flopy4/xarray_jinja/templates/disu_template.disu.jinja
new file mode 100644
index 0000000..f80495c
--- /dev/null
+++ b/flopy4/xarray_jinja/templates/disu_template.disu.jinja
@@ -0,0 +1,5 @@
+BEGIN GRIDDATA
+{% for chunk in data | dask_expand %}
+{{chunk | nparray2string }}
+{% endfor %}
+END GRIDDATA
diff --git a/test/test_xarray_jinja.py b/test/test_xarray_jinja.py
new file mode 100644
index 0000000..d4090b3
--- /dev/null
+++ b/test/test_xarray_jinja.py
@@ -0,0 +1,28 @@
+import dask.array as da
+import jinja2
+import xarray as xr
+
+import flopy4.xarray_jinja.filters as filters
+
+
+def test_xarray_to_text_jinja(tmp_path):
+    data = xr.DataArray(da.arange(0, 10_000, 1), dims="x")
+    data = data.chunk(100)
+
+    env = jinja2.Environment(
+        loader=jinja2.PackageLoader("flopy4.xarray_jinja"),
+        trim_blocks=True,
+        lstrip_blocks=True,
+    )
+    env.filters["dask_expand"] = filters.dask_expand
+    env.filters["nparray2string"] = filters.nparray2string
+
+    generator = env.get_template("disu_template.disu.jinja").generate(
+        data=data
+    )
+    with open(tmp_path / "test_xarray_to_text_jinja.disu", "w") as f:
+        f.writelines(generator)
+
+    with open(tmp_path / "test_xarray_to_text_jinja.disu", "r") as f:
+        output = f.readlines()
+        assert len(output) == 102  # begin + end + 100 lines of data

From 27db7d77f468942c6c00b5c81732ca74c52c5063 Mon Sep 17 00:00:00 2001
From: Marnix <marnix.kraus@deltares.nl>
Date: Thu, 19 Dec 2024 16:37:32 +0100
Subject: [PATCH 02/12] Add different flavors of file IO for dask

---
 flopy4/xarray_jinja/filters.py |   8 +-
 pixi.lock                      | 247 ++++++++++++++++++++++++++-------
 pyproject.toml                 |   1 +
 test/test_xarray_io.py         | 195 ++++++++++++++++++++++++++
 test/test_xarray_jinja.py      |  28 ----
 5 files changed, 395 insertions(+), 84 deletions(-)
 create mode 100644 test/test_xarray_io.py
 delete mode 100644 test/test_xarray_jinja.py

diff --git a/flopy4/xarray_jinja/filters.py b/flopy4/xarray_jinja/filters.py
index 08e0e75..de07c1b 100644
--- a/flopy4/xarray_jinja/filters.py
+++ b/flopy4/xarray_jinja/filters.py
@@ -1,12 +1,16 @@
+import sys
+
 import numpy as np
 import xarray as xr
 
 
 def dask_expand(data: xr.DataArray):
-    for block in data.data.blocks:
+    for block in data.data.to_delayed():
         block_data = block.compute()
         yield block_data
 
 
 def nparray2string(data: np.ndarray):
-    return " ".join(data.astype(str))
+    return np.array2string(
+        data, separator=" ", precision=4, max_line_width=sys.maxsize
+    )[1:-1]  # remove brackets
diff --git a/pixi.lock b/pixi.lock
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       - pypi: https://files.pythonhosted.org/packages/80/ab/11a76c1e2126084fde2639514f24e6111b789b0bfa4fc6264a8975c7e1f1/zict-3.0.0-py2.py3-none-any.whl
@@ -3664,7 +3709,7 @@ packages:
 - pypi: .
   name: flopy4
   version: 0.0.1.dev0
-  sha256: 6347ea98cd5a19d2ee185fbf299b7e0b435a9e5f25854c168af7fcbb718184a6
+  sha256: 4b006a43291f349a9ed013ef25fe59983308087711cd69f5f267db44cccc0a38
   requires_dist:
   - attrs
   - cattrs
@@ -3677,6 +3722,7 @@ packages:
   - networkx>=3.4.2,<4
   - xarray[io,parallel]>=2024.11.0,<2025
   - scipy>=1.14.1,<2
+  - xarray-extras>=0.6.0
   - flopy4[build,lint,test] ; extra == 'dev'
   - ruff ; extra == 'lint'
   - pre-commit>=4.0.1,<5 ; extra == 'lint'
@@ -5367,6 +5413,41 @@ packages:
   purls: []
   size: 55476
   timestamp: 1727963768015
+- pypi: https://files.pythonhosted.org/packages/00/5f/323c4d56e8401c50185fd0e875fcf06b71bf825a863699be1eb10aa2a9cb/llvmlite-0.43.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
+  name: llvmlite
+  version: 0.43.0
+  sha256: df6509e1507ca0760787a199d19439cc887bfd82226f5af746d6977bd9f66844
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/0b/67/9443509e5d2b6d8587bae3ede5598fa8bd586b1c7701696663ea8af15b5b/llvmlite-0.43.0-cp312-cp312-macosx_10_9_x86_64.whl
+  name: llvmlite
+  version: 0.43.0
+  sha256: f99b600aa7f65235a5a05d0b9a9f31150c390f31261f2a0ba678e26823ec38f7
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/20/ab/ed5ed3688c6ba4f0b8d789da19fd8e30a9cf7fc5852effe311bc5aefe73e/llvmlite-0.43.0-cp311-cp311-win_amd64.whl
+  name: llvmlite
+  version: 0.43.0
+  sha256: d5bd550001d26450bd90777736c69d68c487d17bf371438f975229b2b8241a91
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/6b/99/5d00a7d671b1ba1751fc9f19d3b36f3300774c6eebe2bcdb5f6191763eb4/llvmlite-0.43.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
+  name: llvmlite
+  version: 0.43.0
+  sha256: 977525a1e5f4059316b183fb4fd34fa858c9eade31f165427a3977c95e3ee749
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/95/8c/de3276d773ab6ce3ad676df5fab5aac19696b2956319d65d7dd88fb10f19/llvmlite-0.43.0-cp311-cp311-macosx_10_9_x86_64.whl
+  name: llvmlite
+  version: 0.43.0
+  sha256: 3e8d0618cb9bfe40ac38a9633f2493d4d4e9fcc2f438d39a4e854f39cc0f5f98
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/9f/3d/f513755f285db51ab363a53e898b85562e950f79a2e6767a364530c2f645/llvmlite-0.43.0.tar.gz
+  name: llvmlite
+  version: 0.43.0
+  sha256: ae2b5b5c3ef67354824fb75517c8db5fbe93bc02cd9671f3c62271626bc041d5
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/c6/94/dea10e263655ce78d777e78d904903faae39d1fc440762be4a9dc46bed49/llvmlite-0.43.0-cp312-cp312-win_amd64.whl
+  name: llvmlite
+  version: 0.43.0
+  sha256: 7a2872ee80dcf6b5dbdc838763d26554c2a18aa833d31a2635bff16aafefb9c9
+  requires_python: '>=3.9'
 - pypi: https://files.pythonhosted.org/packages/db/bc/83e112abc66cd466c6b83f99118035867cecd41802f8d044638aa78a106e/locket-1.0.0-py2.py3-none-any.whl
   name: locket
   version: 1.0.0
@@ -6288,6 +6369,62 @@ packages:
   - pytest-jupyter ; extra == 'test'
   - pytest-tornasync ; extra == 'test'
   requires_python: '>=3.7'
+- pypi: https://files.pythonhosted.org/packages/3c/93/2849300a9184775ba274aba6f82f303343669b0592b7bb0849ea713dabb0/numba-0.60.0.tar.gz
+  name: numba
+  version: 0.60.0
+  sha256: 5df6158e5584eece5fc83294b949fd30b9f1125df7708862205217e068aabf16
+  requires_dist:
+  - llvmlite>=0.43.0.dev0,<0.44
+  - numpy>=1.22,<2.1
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/57/03/2b4245b05b71c0cee667e6a0b51606dfa7f4157c9093d71c6b208385a611/numba-0.60.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
+  name: numba
+  version: 0.60.0
+  sha256: 4142d7ac0210cc86432b818338a2bc368dc773a2f5cf1e32ff7c5b378bd63ee8
+  requires_dist:
+  - llvmlite>=0.43.0.dev0,<0.44
+  - numpy>=1.22,<2.1
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/79/89/2d924ca60dbf949f18a6fec223a2445f5f428d9a5f97a6b29c2122319015/numba-0.60.0-cp311-cp311-win_amd64.whl
+  name: numba
+  version: 0.60.0
+  sha256: cac02c041e9b5bc8cf8f2034ff6f0dbafccd1ae9590dc146b3a02a45e53af4e2
+  requires_dist:
+  - llvmlite>=0.43.0.dev0,<0.44
+  - numpy>=1.22,<2.1
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/8b/41/ac11cf33524def12aa5bd698226ae196a1185831c05ed29dc0c56eaa308b/numba-0.60.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
+  name: numba
+  version: 0.60.0
+  sha256: 0ebaa91538e996f708f1ab30ef4d3ddc344b64b5227b67a57aa74f401bb68b9d
+  requires_dist:
+  - llvmlite>=0.43.0.dev0,<0.44
+  - numpy>=1.22,<2.1
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/98/ad/df18d492a8f00d29a30db307904b9b296e37507034eedb523876f3a2e13e/numba-0.60.0-cp311-cp311-macosx_10_9_x86_64.whl
+  name: numba
+  version: 0.60.0
+  sha256: a17b70fc9e380ee29c42717e8cc0bfaa5556c416d94f9aa96ba13acb41bdece8
+  requires_dist:
+  - llvmlite>=0.43.0.dev0,<0.44
+  - numpy>=1.22,<2.1
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/ca/bd/0fe29fcd1b6a8de479a4ed25c6e56470e467e3611c079d55869ceef2b6d1/numba-0.60.0-cp312-cp312-win_amd64.whl
+  name: numba
+  version: 0.60.0
+  sha256: f75262e8fe7fa96db1dca93d53a194a38c46da28b112b8a4aca168f0df860347
+  requires_dist:
+  - llvmlite>=0.43.0.dev0,<0.44
+  - numpy>=1.22,<2.1
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/eb/5c/b5ec752c475e78a6c3676b67c514220dbde2725896bbb0b6ec6ea54b2738/numba-0.60.0-cp312-cp312-macosx_10_9_x86_64.whl
+  name: numba
+  version: 0.60.0
+  sha256: d7da4098db31182fc5ffe4bc42c6f24cd7d1cb8a14b59fd755bfee32e34b8404
+  requires_dist:
+  - llvmlite>=0.43.0.dev0,<0.44
+  - numpy>=1.22,<2.1
+  requires_python: '>=3.9'
 - pypi: https://files.pythonhosted.org/packages/45/9e/6d0e62230af971620110063aec6f0328e995bb71160a17760cd721719f33/numcodecs-0.14.1-cp311-cp311-win_amd64.whl
   name: numcodecs
   version: 0.14.1
@@ -6468,51 +6605,41 @@ packages:
   - pcodec>=0.2,<0.3 ; extra == 'pcodec'
   - crc32c>=2.7 ; extra == 'crc32c'
   requires_python: '>=3.11'
-- pypi: https://files.pythonhosted.org/packages/30/04/e1ee6f8b22034302d4c5c24e15782bdedf76d90b90f3874ed0b48525def0/numpy-2.2.0-cp313-cp313-win_amd64.whl
+- pypi: https://files.pythonhosted.org/packages/39/68/e9f1126d757653496dbc096cb429014347a36b228f5a991dae2c6b6cfd40/numpy-2.0.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
   name: numpy
-  version: 2.2.0
-  sha256: a184288538e6ad699cbe6b24859206e38ce5fba28f3bcfa51c90d0502c1582b2
-  requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/52/33/10825f580f42a353f744abc450dcd2a4b1e6f1931abb0ccbd1d63bd3993c/numpy-2.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
-  name: numpy
-  version: 2.2.0
-  sha256: c2aed8fcf8abc3020d6a9ccb31dbc9e7d7819c56a348cc88fd44be269b37427e
-  requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/7f/bc/a20dc4e1d051149052762e7647455311865d11c603170c476d1e910a353e/numpy-2.2.0-cp312-cp312-macosx_10_13_x86_64.whl
-  name: numpy
-  version: 2.2.0
-  sha256: cff210198bb4cae3f3c100444c5eaa573a823f05c253e7188e1362a5555235b3
-  requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/80/1b/736023977a96e787c4e7653a1ac2d31d4f6ab6b4048f83c8359f7c0af2e3/numpy-2.2.0-cp311-cp311-macosx_10_9_x86_64.whl
+  version: 2.0.2
+  sha256: 0123ffdaa88fa4ab64835dcbde75dcdf89c453c922f18dced6e27c90d1d0ec5a
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/45/40/2e117be60ec50d98fa08c2f8c48e09b3edea93cfcabd5a9ff6925d54b1c2/numpy-2.0.2-cp312-cp312-macosx_10_9_x86_64.whl
   name: numpy
-  version: 2.2.0
-  sha256: 9874bc2ff574c40ab7a5cbb7464bf9b045d617e36754a7bc93f933d52bd9ffc6
-  requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/89/ea/00537f599eb230771157bc509f6ea5b2dddf05d4b09f9d2f1d7096a18781/numpy-2.2.0-cp312-cp312-win_amd64.whl
+  version: 2.0.2
+  sha256: df55d490dea7934f330006d0f81e8551ba6010a5bf035a249ef61a94f21c500b
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/8b/cf/034500fb83041aa0286e0fb16e7c76e5c8b67c0711bb6e9e9737a717d5fe/numpy-2.0.2-cp311-cp311-macosx_10_9_x86_64.whl
   name: numpy
-  version: 2.2.0
-  sha256: 3a4199f519e57d517ebd48cb76b36c82da0360781c6a0353e64c0cac30ecaad3
-  requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/90/24/d0bbb56abdd8934f30384632e3c2ca1ebfeb5d17e150c6e366ba291de36b/numpy-2.2.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
+  version: 2.0.2
+  sha256: 49ca4decb342d66018b01932139c0961a8f9ddc7589611158cb3c27cbcf76448
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/a9/75/10dd1f8116a8b796cb2c737b674e02d02e80454bda953fa7e65d8c12b016/numpy-2.0.2.tar.gz
   name: numpy
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-  sha256: 85ad7d11b309bd132d74397fcf2920933c9d1dc865487128f5c03d580f2c3d03
-  requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/bd/4c/0d1eef206545c994289e7a9de21b642880a11e0ed47a2b0c407c688c4f69/numpy-2.2.0-cp313-cp313-macosx_10_13_x86_64.whl
+  version: 2.0.2
+  sha256: 883c987dee1880e2a864ab0dc9892292582510604156762362d9326444636e78
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/b2/b5/4ac39baebf1fdb2e72585c8352c56d063b6126be9fc95bd2bb5ef5770c20/numpy-2.0.2-cp312-cp312-win_amd64.whl
   name: numpy
-  version: 2.2.0
-  sha256: f8c8b141ef9699ae777c6278b52c706b653bf15d135d302754f6b2e90eb30367
-  requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/d0/06/3d1ff6ed377cb0340baf90487a35f15f9dc1db8e0a07de2bf2c54a8e490f/numpy-2.2.0-cp311-cp311-win_amd64.whl
+  version: 2.0.2
+  sha256: cfd41e13fdc257aa5778496b8caa5e856dc4896d4ccf01841daee1d96465467a
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/ba/a8/c17acf65a931ce551fee11b72e8de63bf7e8a6f0e21add4c937c83563538/numpy-2.0.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
   name: numpy
-  version: 2.2.0
-  sha256: 16757cf28621e43e252c560d25b15f18a2f11da94fea344bf26c599b9cf54b73
-  requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/df/54/13535f74391dbe5f479ceed96f1403267be302c840040700d4fd66688089/numpy-2.2.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
+  version: 2.0.2
+  sha256: 13e689d772146140a252c3a28501da66dfecd77490b498b168b501835041f951
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/eb/57/3a3f14d3a759dcf9bf6e9eda905794726b758819df4663f217d658a58695/numpy-2.0.2-cp311-cp311-win_amd64.whl
   name: numpy
-  version: 2.2.0
-  sha256: a7d41d1612c1a82b64697e894b75db6758d4f21c3ec069d841e60ebe54b5b571
-  requires_python: '>=3.10'
+  version: 2.0.2
+  sha256: 286cd40ce2b7d652a6f22efdfc6d1edf879440e53e76a75955bc0c826c7e64dc
+  requires_python: '>=3.9'
 - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.4.0-hb9d3cd8_0.conda
   sha256: 814b9dff1847b132c676ee6cc1a8cb2d427320779b93e1b6d76552275c128705
   md5: 23cc74f77eb99315c0360ec3533147a9
@@ -9408,6 +9535,18 @@ packages:
   - nc-time-axis ; extra == 'viz'
   - seaborn ; extra == 'viz'
   requires_python: '>=3.10'
+- pypi: https://files.pythonhosted.org/packages/5e/2f/22de7d2c53b47f3135c3268ea3a2a6580d5a6aa8db14d386d42b7678e512/xarray_extras-0.6.0.tar.gz
+  name: xarray-extras
+  version: 0.6.0
+  sha256: 825f86ecacfc5fd0e36f881ec974da9e8d1d7a5f6e0ede866142defddae4a749
+  requires_dist:
+  - dask>=2022.6.0
+  - numba>=0.56
+  - numpy>=1.23
+  - pandas>=1.5
+  - scipy>=1.9
+  - xarray>=2022.11.0
+  requires_python: '>=3.8'
 - pypi: https://files.pythonhosted.org/packages/4c/d3/e07ce413d16ef64e885bea37551eac4c5ca3ddd440933f9c94594273d0d9/xyzservices-2024.9.0-py3-none-any.whl
   name: xyzservices
   version: 2024.9.0
diff --git a/pyproject.toml b/pyproject.toml
index d196f86..05f8eb6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -45,6 +45,7 @@ dependencies = [
     "networkx>=3.4.2,<4",
     "xarray[parallel,io]>=2024.11.0,<2025",
     "scipy>=1.14.1,<2",
+    "xarray-extras>=0.6.0",
 ]
 dynamic = ["version"]
 
diff --git a/test/test_xarray_io.py b/test/test_xarray_io.py
new file mode 100644
index 0000000..2483aac
--- /dev/null
+++ b/test/test_xarray_io.py
@@ -0,0 +1,195 @@
+import time
+from typing import Any, Callable, Tuple
+
+import dask.array as da
+import jinja2
+import numpy as np
+import pytest
+import xarray as xr
+import xarray_extras
+import xarray_extras.csv
+
+import flopy4.xarray_jinja.filters as filters
+
+test_combinations = [
+    (1_000, 100),
+    (1_000_000, 1_000),
+    (1_000_000, 10_000),
+    (10_000_000, 1_000),
+    (10_000_000, 10_000),
+    (100_000_000, 10_000),
+    (100_000_000, 100_000),
+]
+
+
+@pytest.fixture(scope="module")
+def memory_file():
+    with open("memory.md", "w") as f:
+        f.write("| test | args | memory (MB) | \n")
+        f.write("| --- | --- | --- | \n")
+        yield f
+
+
+@pytest.fixture(scope="module")
+def time_file():
+    with open("times.md", "w") as f:
+        f.write("| test | args | time (s) | \n")
+        f.write("| --- | --- | --- | \n")
+        yield f
+
+
+def profile_function(
+    func: Callable,
+    args: Tuple[Any, ...],
+    memory_file,
+    time_file,
+    print_args={},
+) -> None:
+    start_time = time.time()
+    func(*args)
+    end_time = time.time()
+
+    name = getattr(func, "__name__", "unknown")
+    time_file.write(f"| {name} | {print_args} | {end_time - start_time} |\n")
+
+
+def create_and_write_jinja(tmp_path, data: xr.DataArray):
+    env = jinja2.Environment(
+        loader=jinja2.PackageLoader("flopy4.xarray_jinja"),
+        trim_blocks=True,
+        lstrip_blocks=True,
+    )
+    env.filters["dask_expand"] = filters.dask_expand
+    env.filters["nparray2string"] = filters.nparray2string
+
+    generator = env.get_template("disu_template.disu.jinja").generate(
+        data=data
+    )
+    with open(tmp_path / "test_xarray_to_text_jinja.disu", "w") as f:
+        f.writelines(generator)
+
+
+@pytest.mark.parametrize(
+    "max_size,chunks",
+    test_combinations,
+)
+def test_xarray_to_text_jinja(
+    tmp_path, max_size, chunks, time_file, memory_file
+):
+    data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
+    data = data.chunk(chunks)
+    profile_function(
+        create_and_write_jinja,
+        (tmp_path, data),
+        memory_file,
+        time_file,
+        print_args={"max_size": max_size, "chunks": chunks},
+    )
+
+    with open(tmp_path / "test_xarray_to_text_jinja.disu", "r") as f:
+        output = f.readlines()
+        assert (
+            len(output) == 2 + max_size / chunks
+        )  # begin + end + lines of data
+
+
+def create_and_write_pandas(tmp_path, data: xr.DataArray):
+    pandas_data = data.to_pandas()
+    with open(tmp_path / "test_xarray_to_text_extras.disu", "w") as f:
+        f.write("BEGIN GRIDDATA\n")
+        pandas_data.to_csv(
+            f,
+            header=False,
+            index=False,
+            lineterminator=" ",
+            float_format="%.4f",
+        )
+        f.write("\nEND GRIDDATA\n")
+
+
+@pytest.mark.parametrize(
+    "max_size,chunks",
+    test_combinations,
+)
+def test_xarray_to_text_pandas(
+    tmp_path, max_size, chunks, memory_file, time_file
+):
+    data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
+    data = data.chunk(chunks)
+    profile_function(
+        create_and_write_pandas,
+        (tmp_path, data),
+        memory_file,
+        time_file,
+        print_args={"max_size": max_size, "chunks": chunks},
+    )
+
+    with open(tmp_path / "test_xarray_to_text_extras.disu", "r") as f:
+        output = f.readlines()
+        assert len(output) == 3  # begin + end + 1 line of data
+
+
+def create_and_write_np_savetxt(tmp_path, data: xr.DataArray):
+    with open(tmp_path / "test_xarray_to_text_raw.disu", "w") as f:
+        f.write("BEGIN GRIDDATA\n")
+        for block in data.data.to_delayed():
+            block_data = block.compute()
+            np.savetxt(f, block_data, newline=" ", fmt="%.4f")
+        f.write("\nEND GRIDDATA\n")
+
+
+@pytest.mark.parametrize(
+    "max_size,chunks",
+    test_combinations,
+)
+def test_xarray_to_text_np_savetxt(
+    tmp_path, max_size, chunks, memory_file, time_file
+):
+    data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
+    data = data.chunk(chunks)
+    profile_function(
+        create_and_write_np_savetxt,
+        (tmp_path, data),
+        memory_file,
+        time_file,
+        print_args={"max_size": max_size, "chunks": chunks},
+    )
+
+    with open(tmp_path / "test_xarray_to_text_raw.disu", "r") as f:
+        output = f.readlines()
+        assert len(output) == 3
+
+
+def create_and_write_extras(tmp_path, data: xr.DataArray):
+    promise = xarray_extras.csv.to_csv(
+        data,
+        tmp_path / "test_xarray_to_text_extras.disu",
+        header=False,
+        index=False,
+        float_format="%.4f",
+        lineterminator=" ",
+        compression=None,
+    )
+    promise.compute()
+
+
+@pytest.mark.parametrize(
+    "max_size,chunks",
+    test_combinations,
+)
+def test_xarray_to_text_extras(
+    tmp_path, max_size, chunks, memory_file, time_file
+):
+    data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
+    data = data.chunk(chunks)
+    profile_function(
+        create_and_write_extras,
+        (tmp_path, data),
+        memory_file,
+        time_file,
+        print_args={"max_size": max_size, "chunks": chunks},
+    )
+
+    with open(tmp_path / "test_xarray_to_text_extras.disu", "r") as f:
+        output = f.readlines()
+        assert len(output) == 1
diff --git a/test/test_xarray_jinja.py b/test/test_xarray_jinja.py
deleted file mode 100644
index d4090b3..0000000
--- a/test/test_xarray_jinja.py
+++ /dev/null
@@ -1,28 +0,0 @@
-import dask.array as da
-import jinja2
-import xarray as xr
-
-import flopy4.xarray_jinja.filters as filters
-
-
-def test_xarray_to_text_jinja(tmp_path):
-    data = xr.DataArray(da.arange(0, 10_000, 1), dims="x")
-    data = data.chunk(100)
-
-    env = jinja2.Environment(
-        loader=jinja2.PackageLoader("flopy4.xarray_jinja"),
-        trim_blocks=True,
-        lstrip_blocks=True,
-    )
-    env.filters["dask_expand"] = filters.dask_expand
-    env.filters["nparray2string"] = filters.nparray2string
-
-    generator = env.get_template("disu_template.disu.jinja").generate(
-        data=data
-    )
-    with open(tmp_path / "test_xarray_to_text_jinja.disu", "w") as f:
-        f.writelines(generator)
-
-    with open(tmp_path / "test_xarray_to_text_jinja.disu", "r") as f:
-        output = f.readlines()
-        assert len(output) == 102  # begin + end + 100 lines of data

From 5a92a4f8446b3a620e1fe839cf1fae11b64b0ddf Mon Sep 17 00:00:00 2001
From: Marnix <marnix.kraus@deltares.nl>
Date: Thu, 19 Dec 2024 16:58:52 +0100
Subject: [PATCH 03/12] Move print options to the test setup

---
 flopy4/xarray_jinja/filters.py | 6 +-----
 test/test_xarray_io.py         | 5 +++--
 2 files changed, 4 insertions(+), 7 deletions(-)

diff --git a/flopy4/xarray_jinja/filters.py b/flopy4/xarray_jinja/filters.py
index de07c1b..01c301b 100644
--- a/flopy4/xarray_jinja/filters.py
+++ b/flopy4/xarray_jinja/filters.py
@@ -1,5 +1,3 @@
-import sys
-
 import numpy as np
 import xarray as xr
 
@@ -11,6 +9,4 @@ def dask_expand(data: xr.DataArray):
 
 
 def nparray2string(data: np.ndarray):
-    return np.array2string(
-        data, separator=" ", precision=4, max_line_width=sys.maxsize
-    )[1:-1]  # remove brackets
+    return np.array2string(data, separator=" ")[1:-1]  # remove brackets
diff --git a/test/test_xarray_io.py b/test/test_xarray_io.py
index 2483aac..da2ca06 100644
--- a/test/test_xarray_io.py
+++ b/test/test_xarray_io.py
@@ -65,8 +65,9 @@ def create_and_write_jinja(tmp_path, data: xr.DataArray):
     generator = env.get_template("disu_template.disu.jinja").generate(
         data=data
     )
-    with open(tmp_path / "test_xarray_to_text_jinja.disu", "w") as f:
-        f.writelines(generator)
+    with np.printoptions(precision=4, linewidth=sys.maxsize):
+        with open(tmp_path / "test_xarray_to_text_jinja.disu", "w") as f:
+            f.writelines(generator)
 
 
 @pytest.mark.parametrize(

From 735a0d1241b6e00c1a4835d976deec6515dc749d Mon Sep 17 00:00:00 2001
From: Marnix <marnix.kraus@deltares.nl>
Date: Fri, 20 Dec 2024 11:31:38 +0100
Subject: [PATCH 04/12] Make xarray io test work with larger datasets

---
 test/test_xarray_io.py | 28 ++++++++++++++++++++++------
 1 file changed, 22 insertions(+), 6 deletions(-)

diff --git a/test/test_xarray_io.py b/test/test_xarray_io.py
index da2ca06..a64de10 100644
--- a/test/test_xarray_io.py
+++ b/test/test_xarray_io.py
@@ -1,3 +1,4 @@
+import sys
 import time
 from typing import Any, Callable, Tuple
 
@@ -12,13 +13,18 @@
 import flopy4.xarray_jinja.filters as filters
 
 test_combinations = [
-    (1_000, 100),
-    (1_000_000, 1_000),
+    # (1_000, 100),
+    # (1_000_000, 1_000),
     (1_000_000, 10_000),
-    (10_000_000, 1_000),
+    # (10_000_000, 1_000),
     (10_000_000, 10_000),
-    (100_000_000, 10_000),
+    # (100_000_000, 10_000),
     (100_000_000, 100_000),
+    (100_000_000, 1_000_000),  # 1_000_000 is about 8MB of chunks.
+    (
+        100_000_000,
+        10_000_000,
+    ),  # 10_000_000 is about 80MB of chunks. Copilot advised 100MB.
 ]
 
 
@@ -74,6 +80,7 @@ def create_and_write_jinja(tmp_path, data: xr.DataArray):
     "max_size,chunks",
     test_combinations,
 )
+@pytest.mark.skip("Too slow for large data")
 def test_xarray_to_text_jinja(
     tmp_path, max_size, chunks, time_file, memory_file
 ):
@@ -143,6 +150,7 @@ def create_and_write_np_savetxt(tmp_path, data: xr.DataArray):
     "max_size,chunks",
     test_combinations,
 )
+@pytest.mark.skip("Too slow for large data")
 def test_xarray_to_text_np_savetxt(
     tmp_path, max_size, chunks, memory_file, time_file
 ):
@@ -162,16 +170,24 @@ def test_xarray_to_text_np_savetxt(
 
 
 def create_and_write_extras(tmp_path, data: xr.DataArray):
+    file_path = tmp_path / "test_xarray_to_text_extras.disu"
+    with open(file_path, "w") as f:
+        f.write("BEGIN GRIDDATA\n")
     promise = xarray_extras.csv.to_csv(
         data,
-        tmp_path / "test_xarray_to_text_extras.disu",
+        file_path,
         header=False,
         index=False,
         float_format="%.4f",
         lineterminator=" ",
         compression=None,
+        mode="a",
     )
     promise.compute()
+    # we have to open the file again,
+    # because xarray_extras only allows paths and no file handlers.
+    with open(file_path, "a") as f:
+        f.write("\nEND GRIDDATA\n")
 
 
 @pytest.mark.parametrize(
@@ -193,4 +209,4 @@ def test_xarray_to_text_extras(
 
     with open(tmp_path / "test_xarray_to_text_extras.disu", "r") as f:
         output = f.readlines()
-        assert len(output) == 1
+        assert len(output) == 3

From 3246316ab87fbcf6773ba68c522dbc2628a3c554 Mon Sep 17 00:00:00 2001
From: Marnix <marnix.kraus@deltares.nl>
Date: Fri, 20 Dec 2024 11:45:18 +0100
Subject: [PATCH 05/12] Remove memory profiling file from the tests

---
 test/test_xarray_io.py | 21 ++++-----------------
 1 file changed, 4 insertions(+), 17 deletions(-)

diff --git a/test/test_xarray_io.py b/test/test_xarray_io.py
index a64de10..400f6d6 100644
--- a/test/test_xarray_io.py
+++ b/test/test_xarray_io.py
@@ -47,7 +47,6 @@ def time_file():
 def profile_function(
     func: Callable,
     args: Tuple[Any, ...],
-    memory_file,
     time_file,
     print_args={},
 ) -> None:
@@ -81,15 +80,12 @@ def create_and_write_jinja(tmp_path, data: xr.DataArray):
     test_combinations,
 )
 @pytest.mark.skip("Too slow for large data")
-def test_xarray_to_text_jinja(
-    tmp_path, max_size, chunks, time_file, memory_file
-):
+def test_xarray_to_text_jinja(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
     profile_function(
         create_and_write_jinja,
         (tmp_path, data),
-        memory_file,
         time_file,
         print_args={"max_size": max_size, "chunks": chunks},
     )
@@ -119,15 +115,12 @@ def create_and_write_pandas(tmp_path, data: xr.DataArray):
     "max_size,chunks",
     test_combinations,
 )
-def test_xarray_to_text_pandas(
-    tmp_path, max_size, chunks, memory_file, time_file
-):
+def test_xarray_to_text_pandas(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
     profile_function(
         create_and_write_pandas,
         (tmp_path, data),
-        memory_file,
         time_file,
         print_args={"max_size": max_size, "chunks": chunks},
     )
@@ -151,15 +144,12 @@ def create_and_write_np_savetxt(tmp_path, data: xr.DataArray):
     test_combinations,
 )
 @pytest.mark.skip("Too slow for large data")
-def test_xarray_to_text_np_savetxt(
-    tmp_path, max_size, chunks, memory_file, time_file
-):
+def test_xarray_to_text_np_savetxt(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
     profile_function(
         create_and_write_np_savetxt,
         (tmp_path, data),
-        memory_file,
         time_file,
         print_args={"max_size": max_size, "chunks": chunks},
     )
@@ -194,15 +184,12 @@ def create_and_write_extras(tmp_path, data: xr.DataArray):
     "max_size,chunks",
     test_combinations,
 )
-def test_xarray_to_text_extras(
-    tmp_path, max_size, chunks, memory_file, time_file
-):
+def test_xarray_to_text_extras(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
     profile_function(
         create_and_write_extras,
         (tmp_path, data),
-        memory_file,
         time_file,
         print_args={"max_size": max_size, "chunks": chunks},
     )

From aac221c5b479386281b9437c3def48df84d2b123 Mon Sep 17 00:00:00 2001
From: Marnix <marnix.kraus@deltares.nl>
Date: Mon, 23 Dec 2024 14:37:36 +0100
Subject: [PATCH 06/12] Add memory profiling test

---
 .vscode/settings.json  |  5 +++--
 pytest.ini             |  4 ++++
 test/test_xarray_io.py | 45 ++++++++++++++++++++++++++++++++++++++++++
 3 files changed, 52 insertions(+), 2 deletions(-)
 create mode 100644 pytest.ini

diff --git a/.vscode/settings.json b/.vscode/settings.json
index 3f206a5..261c738 100644
--- a/.vscode/settings.json
+++ b/.vscode/settings.json
@@ -10,5 +10,6 @@
         "editor.codeActionsOnSave": {
             "source.fixAll": "explicit"
         }
-    }
-}
\ No newline at end of file
+    },
+    "files.insertFinalNewline": true,
+}
diff --git a/pytest.ini b/pytest.ini
new file mode 100644
index 0000000..ddf98be
--- /dev/null
+++ b/pytest.ini
@@ -0,0 +1,4 @@
+[pytest]
+markers =
+    timing: mark test as time profiling test
+    memory: mark test as memory profiling test
diff --git a/test/test_xarray_io.py b/test/test_xarray_io.py
index 400f6d6..63d227e 100644
--- a/test/test_xarray_io.py
+++ b/test/test_xarray_io.py
@@ -1,5 +1,6 @@
 import sys
 import time
+import tracemalloc
 from typing import Any, Callable, Tuple
 
 import dask.array as da
@@ -58,6 +59,26 @@ def profile_function(
     time_file.write(f"| {name} | {print_args} | {end_time - start_time} |\n")
 
 
+def mem_check_function(
+    func: Callable,
+    args: Tuple[Any, ...],
+    memory_file,
+    print_args={},
+) -> None:
+    tracemalloc.start()
+    func(*args)
+    snapshot = tracemalloc.take_snapshot()
+    tracemalloc.stop()
+
+    stats_formatted = "".join(
+        [f"<li>{s}</li>" for s in snapshot.statistics("lineno")[:10]]
+    )
+    name = getattr(func, "__name__", "unknown")
+    memory_file.write(
+        f"| {name} | {print_args} | <ol>{stats_formatted}</ol> |\n"
+    )
+
+
 def create_and_write_jinja(tmp_path, data: xr.DataArray):
     env = jinja2.Environment(
         loader=jinja2.PackageLoader("flopy4.xarray_jinja"),
@@ -80,6 +101,7 @@ def create_and_write_jinja(tmp_path, data: xr.DataArray):
     test_combinations,
 )
 @pytest.mark.skip("Too slow for large data")
+@pytest.mark.timing
 def test_xarray_to_text_jinja(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
@@ -115,6 +137,7 @@ def create_and_write_pandas(tmp_path, data: xr.DataArray):
     "max_size,chunks",
     test_combinations,
 )
+@pytest.mark.timing
 def test_xarray_to_text_pandas(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
@@ -144,6 +167,7 @@ def create_and_write_np_savetxt(tmp_path, data: xr.DataArray):
     test_combinations,
 )
 @pytest.mark.skip("Too slow for large data")
+@pytest.mark.timing
 def test_xarray_to_text_np_savetxt(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
@@ -184,6 +208,7 @@ def create_and_write_extras(tmp_path, data: xr.DataArray):
     "max_size,chunks",
     test_combinations,
 )
+@pytest.mark.timing
 def test_xarray_to_text_extras(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
@@ -197,3 +222,23 @@ def test_xarray_to_text_extras(tmp_path, max_size, chunks, time_file):
     with open(tmp_path / "test_xarray_to_text_extras.disu", "r") as f:
         output = f.readlines()
         assert len(output) == 3
+
+
+@pytest.mark.parametrize(
+    "max_size,chunks",
+    test_combinations,
+)
+@pytest.mark.memory
+def test_xarray_to_text_extras_mem(tmp_path, max_size, chunks, memory_file):
+    data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
+    data = data.chunk(chunks)
+    mem_check_function(
+        create_and_write_extras,
+        (tmp_path, data),
+        memory_file,
+        print_args={"max_size": max_size, "chunks": chunks},
+    )
+
+    with open(tmp_path / "test_xarray_to_text_extras.disu", "r") as f:
+        output = f.readlines()
+        assert len(output) == 3

From 51fafa23151d6775fbb65e4fca1b0665392a10a1 Mon Sep 17 00:00:00 2001
From: Marnix <marnix.kraus@deltares.nl>
Date: Mon, 23 Dec 2024 14:46:15 +0100
Subject: [PATCH 07/12] Simplify file path usage

---
 test/test_xarray_io.py | 70 +++++++++++++++++++-----------------------
 1 file changed, 32 insertions(+), 38 deletions(-)

diff --git a/test/test_xarray_io.py b/test/test_xarray_io.py
index 63d227e..9225ccd 100644
--- a/test/test_xarray_io.py
+++ b/test/test_xarray_io.py
@@ -79,7 +79,7 @@ def mem_check_function(
     )
 
 
-def create_and_write_jinja(tmp_path, data: xr.DataArray):
+def create_and_write_jinja(file_path, data: xr.DataArray):
     env = jinja2.Environment(
         loader=jinja2.PackageLoader("flopy4.xarray_jinja"),
         trim_blocks=True,
@@ -92,36 +92,35 @@ def create_and_write_jinja(tmp_path, data: xr.DataArray):
         data=data
     )
     with np.printoptions(precision=4, linewidth=sys.maxsize):
-        with open(tmp_path / "test_xarray_to_text_jinja.disu", "w") as f:
+        with open(file_path, "w") as f:
             f.writelines(generator)
 
 
-@pytest.mark.parametrize(
-    "max_size,chunks",
-    test_combinations,
-)
+@pytest.mark.parametrize("max_size,chunks", test_combinations)
 @pytest.mark.skip("Too slow for large data")
 @pytest.mark.timing
 def test_xarray_to_text_jinja(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
+    file_path = tmp_path / "test_xarray_to_text_jinja.disu"
+
     profile_function(
         create_and_write_jinja,
-        (tmp_path, data),
+        (file_path, data),
         time_file,
         print_args={"max_size": max_size, "chunks": chunks},
     )
 
-    with open(tmp_path / "test_xarray_to_text_jinja.disu", "r") as f:
+    with open(file_path, "r") as f:
         output = f.readlines()
         assert (
             len(output) == 2 + max_size / chunks
         )  # begin + end + lines of data
 
 
-def create_and_write_pandas(tmp_path, data: xr.DataArray):
+def create_and_write_pandas(file_path, data: xr.DataArray):
     pandas_data = data.to_pandas()
-    with open(tmp_path / "test_xarray_to_text_extras.disu", "w") as f:
+    with open(file_path, "w") as f:
         f.write("BEGIN GRIDDATA\n")
         pandas_data.to_csv(
             f,
@@ -133,28 +132,27 @@ def create_and_write_pandas(tmp_path, data: xr.DataArray):
         f.write("\nEND GRIDDATA\n")
 
 
-@pytest.mark.parametrize(
-    "max_size,chunks",
-    test_combinations,
-)
+@pytest.mark.parametrize("max_size,chunks", test_combinations)
 @pytest.mark.timing
 def test_xarray_to_text_pandas(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
+    file_path = tmp_path / "test_xarray_to_text_extras.disu"
+
     profile_function(
         create_and_write_pandas,
-        (tmp_path, data),
+        (file_path, data),
         time_file,
         print_args={"max_size": max_size, "chunks": chunks},
     )
 
-    with open(tmp_path / "test_xarray_to_text_extras.disu", "r") as f:
+    with open(file_path, "r") as f:
         output = f.readlines()
         assert len(output) == 3  # begin + end + 1 line of data
 
 
-def create_and_write_np_savetxt(tmp_path, data: xr.DataArray):
-    with open(tmp_path / "test_xarray_to_text_raw.disu", "w") as f:
+def create_and_write_np_savetxt(file_path, data: xr.DataArray):
+    with open(file_path, "w") as f:
         f.write("BEGIN GRIDDATA\n")
         for block in data.data.to_delayed():
             block_data = block.compute()
@@ -162,29 +160,27 @@ def create_and_write_np_savetxt(tmp_path, data: xr.DataArray):
         f.write("\nEND GRIDDATA\n")
 
 
-@pytest.mark.parametrize(
-    "max_size,chunks",
-    test_combinations,
-)
+@pytest.mark.parametrize("max_size,chunks", test_combinations)
 @pytest.mark.skip("Too slow for large data")
 @pytest.mark.timing
 def test_xarray_to_text_np_savetxt(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
+    file_path = tmp_path / "test_xarray_to_text_raw.disu"
+
     profile_function(
         create_and_write_np_savetxt,
-        (tmp_path, data),
+        (file_path, data),
         time_file,
         print_args={"max_size": max_size, "chunks": chunks},
     )
 
-    with open(tmp_path / "test_xarray_to_text_raw.disu", "r") as f:
+    with open(file_path, "r") as f:
         output = f.readlines()
         assert len(output) == 3
 
 
-def create_and_write_extras(tmp_path, data: xr.DataArray):
-    file_path = tmp_path / "test_xarray_to_text_extras.disu"
+def create_and_write_extras(file_path, data: xr.DataArray):
     with open(file_path, "w") as f:
         f.write("BEGIN GRIDDATA\n")
     promise = xarray_extras.csv.to_csv(
@@ -204,41 +200,39 @@ def create_and_write_extras(tmp_path, data: xr.DataArray):
         f.write("\nEND GRIDDATA\n")
 
 
-@pytest.mark.parametrize(
-    "max_size,chunks",
-    test_combinations,
-)
+@pytest.mark.parametrize("max_size,chunks", test_combinations)
 @pytest.mark.timing
 def test_xarray_to_text_extras(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
+    file_path = tmp_path / "test_xarray_to_text_extras.disu"
+
     profile_function(
         create_and_write_extras,
-        (tmp_path, data),
+        (file_path, data),
         time_file,
         print_args={"max_size": max_size, "chunks": chunks},
     )
 
-    with open(tmp_path / "test_xarray_to_text_extras.disu", "r") as f:
+    with open(file_path, "r") as f:
         output = f.readlines()
         assert len(output) == 3
 
 
-@pytest.mark.parametrize(
-    "max_size,chunks",
-    test_combinations,
-)
+@pytest.mark.parametrize("max_size,chunks", test_combinations)
 @pytest.mark.memory
 def test_xarray_to_text_extras_mem(tmp_path, max_size, chunks, memory_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
+    file_path = tmp_path / "test_xarray_to_text_extras.disu"
+
     mem_check_function(
         create_and_write_extras,
-        (tmp_path, data),
+        (file_path, data),
         memory_file,
         print_args={"max_size": max_size, "chunks": chunks},
     )
 
-    with open(tmp_path / "test_xarray_to_text_extras.disu", "r") as f:
+    with open(file_path, "r") as f:
         output = f.readlines()
         assert len(output) == 3

From 38c5ebf3ce47837a2904b40a55df8bdc057ffc6e Mon Sep 17 00:00:00 2001
From: Marnix <marnix.kraus@deltares.nl>
Date: Thu, 2 Jan 2025 12:59:38 +0100
Subject: [PATCH 08/12] Merge pytest.ini files

---
 pytest.ini      | 4 ----
 test/pytest.ini | 4 +++-
 2 files changed, 3 insertions(+), 5 deletions(-)
 delete mode 100644 pytest.ini

diff --git a/pytest.ini b/pytest.ini
deleted file mode 100644
index ddf98be..0000000
--- a/pytest.ini
+++ /dev/null
@@ -1,4 +0,0 @@
-[pytest]
-markers =
-    timing: mark test as time profiling test
-    memory: mark test as memory profiling test
diff --git a/test/pytest.ini b/test/pytest.ini
index 286b921..e57c88d 100644
--- a/test/pytest.ini
+++ b/test/pytest.ini
@@ -3,4 +3,6 @@ addopts = --color=yes
 python_files =
     test_*.py
 markers =
-    slow: tests not completing in a few seconds
\ No newline at end of file
+    slow: tests not completing in a few seconds
+    timing: mark test as time profiling test
+    memory: mark test as memory profiling test

From 5110ee9a381ee60f7aa6298839d513d31a08c65a Mon Sep 17 00:00:00 2001
From: Marnix <marnix.kraus@deltares.nl>
Date: Fri, 3 Jan 2025 14:54:19 +0100
Subject: [PATCH 09/12] Add more memory tests, but skip them in the main test
 flow

---
 test/test_xarray_io.py | 112 ++++++++++++++++++++++++++++++++---------
 1 file changed, 89 insertions(+), 23 deletions(-)

diff --git a/test/test_xarray_io.py b/test/test_xarray_io.py
index 9225ccd..7d5175f 100644
--- a/test/test_xarray_io.py
+++ b/test/test_xarray_io.py
@@ -14,34 +14,34 @@
 import flopy4.xarray_jinja.filters as filters
 
 test_combinations = [
-    # (1_000, 100),
-    # (1_000_000, 1_000),
+    (1_000, 100),
+    (1_000_000, 1_000),
     (1_000_000, 10_000),
     # (10_000_000, 1_000),
-    (10_000_000, 10_000),
+    # (10_000_000, 10_000),
     # (100_000_000, 10_000),
-    (100_000_000, 100_000),
-    (100_000_000, 1_000_000),  # 1_000_000 is about 8MB of chunks.
-    (
-        100_000_000,
-        10_000_000,
-    ),  # 10_000_000 is about 80MB of chunks. Copilot advised 100MB.
+    # (100_000_000, 100_000),
+    # (100_000_000, 1_000_000),  # 1_000_000 is about 8MB of chunks.
+    # (
+    #     1_000_000_000,
+    #     10_000_000,
+    # ),  # 10_000_000 is about 80MB of chunks. Copilot advised 100MB.
 ]
 
 
 @pytest.fixture(scope="module")
 def memory_file():
     with open("memory.md", "w") as f:
-        f.write("| test | args | memory (MB) | \n")
-        f.write("| --- | --- | --- | \n")
+        f.write("| test | args | memory (MB) |\n")
+        f.write("| --- | --- | --- |\n")
         yield f
 
 
 @pytest.fixture(scope="module")
 def time_file():
     with open("times.md", "w") as f:
-        f.write("| test | args | time (s) | \n")
-        f.write("| --- | --- | --- | \n")
+        f.write("| test | args | time (s) |\n")
+        f.write("| --- | --- | --- |\n")
         yield f
 
 
@@ -67,16 +67,17 @@ def mem_check_function(
 ) -> None:
     tracemalloc.start()
     func(*args)
-    snapshot = tracemalloc.take_snapshot()
+    size, peak = tracemalloc.get_traced_memory()
     tracemalloc.stop()
 
-    stats_formatted = "".join(
-        [f"<li>{s}</li>" for s in snapshot.statistics("lineno")[:10]]
-    )
     name = getattr(func, "__name__", "unknown")
-    memory_file.write(
-        f"| {name} | {print_args} | <ol>{stats_formatted}</ol> |\n"
-    )
+    # stats_formatted = "".join(
+    #     [f"<li>{s}</li>" for s in snapshot.statistics("lineno")[:10]]
+    # )
+    # memory_file.write(
+    #     f"| {name} | {print_args} | <ol>{stats_formatted}</ol> |\n"
+    # )
+    memory_file.write(f"| {name} | {print_args} | {peak / 10**6} MB |\n")
 
 
 def create_and_write_jinja(file_path, data: xr.DataArray):
@@ -91,13 +92,14 @@ def create_and_write_jinja(file_path, data: xr.DataArray):
     generator = env.get_template("disu_template.disu.jinja").generate(
         data=data
     )
-    with np.printoptions(precision=4, linewidth=sys.maxsize):
+    with np.printoptions(
+        precision=4, linewidth=sys.maxsize, threshold=sys.maxsize
+    ):
         with open(file_path, "w") as f:
             f.writelines(generator)
 
 
 @pytest.mark.parametrize("max_size,chunks", test_combinations)
-@pytest.mark.skip("Too slow for large data")
 @pytest.mark.timing
 def test_xarray_to_text_jinja(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
@@ -161,7 +163,6 @@ def create_and_write_np_savetxt(file_path, data: xr.DataArray):
 
 
 @pytest.mark.parametrize("max_size,chunks", test_combinations)
-@pytest.mark.skip("Too slow for large data")
 @pytest.mark.timing
 def test_xarray_to_text_np_savetxt(tmp_path, max_size, chunks, time_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
@@ -221,6 +222,7 @@ def test_xarray_to_text_extras(tmp_path, max_size, chunks, time_file):
 
 @pytest.mark.parametrize("max_size,chunks", test_combinations)
 @pytest.mark.memory
+@pytest.mark.skip("Memory tests take a long time to run")
 def test_xarray_to_text_extras_mem(tmp_path, max_size, chunks, memory_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
@@ -236,3 +238,67 @@ def test_xarray_to_text_extras_mem(tmp_path, max_size, chunks, memory_file):
     with open(file_path, "r") as f:
         output = f.readlines()
         assert len(output) == 3
+
+
+@pytest.mark.parametrize("max_size,chunks", test_combinations)
+@pytest.mark.memory
+@pytest.mark.skip("Memory tests take a long time to run")
+def test_xarray_to_text_pandas_mem(tmp_path, max_size, chunks, memory_file):
+    data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
+    data = data.chunk(chunks)
+    file_path = tmp_path / "test_xarray_to_text_pandas.disu"
+
+    mem_check_function(
+        create_and_write_pandas,
+        (file_path, data),
+        memory_file,
+        print_args={"max_size": max_size, "chunks": chunks},
+    )
+
+    with open(file_path, "r") as f:
+        output = f.readlines()
+        assert len(output) == 3
+
+
+@pytest.mark.parametrize("max_size,chunks", test_combinations)
+@pytest.mark.memory
+@pytest.mark.skip("Memory tests take a long time to run")
+def test_xarray_to_text_np_savetext_mem(
+    tmp_path, max_size, chunks, memory_file
+):
+    data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
+    data = data.chunk(chunks)
+    file_path = tmp_path / "test_xarray_to_text_np_savetext.disu"
+
+    mem_check_function(
+        create_and_write_np_savetxt,
+        (file_path, data),
+        memory_file,
+        print_args={"max_size": max_size, "chunks": chunks},
+    )
+
+    with open(file_path, "r") as f:
+        output = f.readlines()
+        assert len(output) == 3
+
+
+@pytest.mark.parametrize("max_size,chunks", test_combinations)
+@pytest.mark.memory
+@pytest.mark.skip("Memory tests take a long time to run")
+def test_xarray_to_text_jinja_mem(tmp_path, max_size, chunks, memory_file):
+    data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
+    data = data.chunk(chunks)
+    file_path = tmp_path / "test_xarray_to_text_jinja.disu"
+
+    mem_check_function(
+        create_and_write_jinja,
+        (file_path, data),
+        memory_file,
+        print_args={"max_size": max_size, "chunks": chunks},
+    )
+
+    with open(file_path, "r") as f:
+        output = f.readlines()
+        assert (
+            len(output) == 2 + max_size / chunks
+        )  # begin + end + lines of data

From 19bcb200a22d0e94d167301659144ae79f6b78c5 Mon Sep 17 00:00:00 2001
From: Marnix <marnix.kraus@deltares.nl>
Date: Fri, 3 Jan 2025 15:15:55 +0100
Subject: [PATCH 10/12] Disable python 3.13 until numba 0.61 is released

---
 .github/workflows/ci.yml |   3 +-
 pixi.lock                | 778 +--------------------------------------
 pyproject.toml           |   8 +-
 3 files changed, 8 insertions(+), 781 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 4996999..c4dd70d 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -61,7 +61,8 @@ jobs:
       fail-fast: false
       matrix:
         os: [ ubuntu-22.04, macos-13, windows-2022 ]
-        python: [ "311", "312", "313" ]
+        # Disable py313 until numba is available for python 3.13
+        python: [ "311", "312" ]
     env:
       GCC_V: 11
     steps:
diff --git a/pixi.lock b/pixi.lock
index 33d0e38..784d05c 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -2009,571 +2009,6 @@ environments:
       - pypi: https://files.pythonhosted.org/packages/ed/c9/142095e654c2b97133ff71df60979422717b29738b08bc8a1709a5d5e0d0/zarr-2.18.3-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/80/ab/11a76c1e2126084fde2639514f24e6111b789b0bfa4fc6264a8975c7e1f1/zict-3.0.0-py2.py3-none-any.whl
       - pypi: .
-  test313:
-    channels:
-    - url: https://conda.anaconda.org/conda-forge/
-    indexes:
-    - https://pypi.org/simple
-    packages:
-      linux-64:
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h4bc722e_7.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/ca-certificates-2024.8.30-hbcca054_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.43-h712a8e2_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.6.4-h5888daf_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.2-h7f98852_5.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-14.2.0-h77fa898_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-14.2.0-h69a702a_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-14.2.0-h77fa898_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.6.3-hb9d3cd8_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-devel-5.6.3-hb9d3cd8_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-h4bc722e_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.47.2-hee588c1_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.38.1-h0b41bf4_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-he02047a_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.4.0-hb9d3cd8_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.13.0-h9ebbce0_101_cp313.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/python_abi-3.13-5_cp313.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.2-h8228510_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h4845f30_101.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2024b-hc8b5060_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/xz-5.6.3-hbcc6ac9_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/xz-gpl-tools-5.6.3-hbcc6ac9_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/xz-tools-5.6.3-hb9d3cd8_1.conda
-      - pypi: https://files.pythonhosted.org/packages/a0/7a/4daaf3b6c08ad7ceffea4634ec206faeff697526421c20f07628c7372156/anyio-4.7.0-py3-none-any.whl
-      - pypi: https://files.pythonhosted.org/packages/a4/6a/e8a041599e78b6b3752da48000b14c8d1e8a04ded09c88c714ba047f34f5/argon2_cffi-23.1.0-py3-none-any.whl
-      - pypi: https://files.pythonhosted.org/packages/ec/f7/378254e6dd7ae6f31fe40c8649eea7d4832a42243acaf0f1fff9083b2bed/argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
-      - pypi: https://files.pythonhosted.org/packages/f8/ed/e97229a566617f2ae958a6b13e7cc0f585470eac730a73e9e82c32a3cdd2/arrow-1.3.0-py3-none-any.whl
-      - pypi: https://files.pythonhosted.org/packages/2d/6a/885bc91484e1aa8f618f6f0228d76d0e67000b0fdd6090673b777e311913/asciitree-0.3.3.tar.gz
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-  name: pyzmq
-  version: 26.2.0
-  sha256: bea2acdd8ea4275e1278350ced63da0b166421928276c7c8e3f9729d7402a57b
-  requires_dist:
-  - cffi ; implementation_name == 'pypy'
-  requires_python: '>=3.7'
-- pypi: https://files.pythonhosted.org/packages/92/ae/6cc4657148143412b5819b05e362ae7dd09fb9fe76e2a539dcff3d0386bc/pyzmq-26.2.0-cp313-cp313-win_amd64.whl
-  name: pyzmq
-  version: 26.2.0
-  sha256: 70fc7fcf0410d16ebdda9b26cbd8bf8d803d220a7f3522e060a69a9c87bf7bad
-  requires_dist:
-  - cffi ; implementation_name == 'pypy'
-  requires_python: '>=3.7'
 - pypi: https://files.pythonhosted.org/packages/ab/68/6fb6ae5551846ad5beca295b7bca32bf0a7ce19f135cb30e55fa2314e6b6/pyzmq-26.2.0-cp311-cp311-manylinux_2_28_x86_64.whl
   name: pyzmq
   version: 26.2.0
@@ -8668,11 +7907,6 @@ packages:
   version: 0.22.3
   sha256: d20cfb4e099748ea39e6f7b16c91ab057989712d31761d3300d43134e26e165f
   requires_python: '>=3.9'
-- pypi: https://files.pythonhosted.org/packages/27/fc/403e65e56f65fff25f2973216974976d3f0a5c3f30e53758589b6dc9b79b/rpds_py-0.22.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
-  name: rpds-py
-  version: 0.22.3
-  sha256: 009de23c9c9ee54bf11303a966edf4d9087cd43a6003672e6aa7def643d06518
-  requires_python: '>=3.9'
 - pypi: https://files.pythonhosted.org/packages/75/47/3383ee3bd787a2a5e65a9b9edc37ccf8505c0a00170e3a5e6ea5fbcd97f7/rpds_py-0.22.3-cp312-cp312-macosx_10_12_x86_64.whl
   name: rpds-py
   version: 0.22.3
@@ -8688,16 +7922,6 @@ packages:
   version: 0.22.3
   sha256: 8bd7c8cfc0b8247c8799080fbff54e0b9619e17cdfeb0478ba7295d43f635d7c
   requires_python: '>=3.9'
-- pypi: https://files.pythonhosted.org/packages/cb/f0/d330d08f51126330467edae2fa4efa5cec8923c87551a79299380fdea30d/rpds_py-0.22.3-cp313-cp313-win_amd64.whl
-  name: rpds-py
-  version: 0.22.3
-  sha256: c58e2339def52ef6b71b8f36d13c3688ea23fa093353f3a4fee2556e62086ec9
-  requires_python: '>=3.9'
-- pypi: https://files.pythonhosted.org/packages/d0/bf/36d5cc1f2c609ae6e8bf0fc35949355ca9d8790eceb66e6385680c951e60/rpds_py-0.22.3-cp313-cp313-macosx_10_12_x86_64.whl
-  name: rpds-py
-  version: 0.22.3
-  sha256: ea7433ce7e4bfc3a85654aeb6747babe3f66eaf9a1d0c1e7a4435bbdf27fea84
-  requires_python: '>=3.9'
 - pypi: https://files.pythonhosted.org/packages/e1/78/79c128c3e71abbc8e9739ac27af11dc0f91840a86fce67ff83c65d1ba195/rpds_py-0.22.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
   name: rpds-py
   version: 0.22.3
diff --git a/pyproject.toml b/pyproject.toml
index 05f8eb6..f5ef73e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -121,13 +121,15 @@ python = "3.11"
 [tool.pixi.feature.py312.dependencies]
 python = "3.12"
 
-[tool.pixi.feature.py313.dependencies]
-python = "3.13"
+# Disable py313 until numba is available for python 3.13
+# [tool.pixi.feature.py313.dependencies]
+# python = "3.13"
 
 [tool.pixi.environments]
 test311 = { features = ["py311", "test"], solve-group = "py311" }
 test312 = { features = ["py312", "test"], solve-group = "py312" }
-test313 = { features = ["py313", "test"], solve-group = "py313" }
+# Disable py313 until numba is available for python 3.13
+# test313 = { features = ["py313", "test"], solve-group = "py313" }
 dev = { features = ["py311", "test", "lint", "build"], solve-group = "py311" }
 
 [tool.pixi.feature.build.tasks]

From 5b0224741b78a7307ffda655927d834fe21bb2fb Mon Sep 17 00:00:00 2001
From: Marnix <marnix.kraus@deltares.nl>
Date: Mon, 6 Jan 2025 08:15:22 +0100
Subject: [PATCH 11/12] Add extra tests for binary writing

---
 test/test_xarray_io.py | 82 ++++++++++++++++++++++++++++++++++++------
 1 file changed, 72 insertions(+), 10 deletions(-)

diff --git a/test/test_xarray_io.py b/test/test_xarray_io.py
index 7d5175f..6da7b33 100644
--- a/test/test_xarray_io.py
+++ b/test/test_xarray_io.py
@@ -220,16 +220,60 @@ def test_xarray_to_text_extras(tmp_path, max_size, chunks, time_file):
         assert len(output) == 3
 
 
+def create_and_write_flatten(file_path, data: xr.DataArray):
+    with open(file_path, "w") as f:
+        data.values.flatten().astype(np.int32).tofile(f)
+
+
+@pytest.mark.parametrize("max_size,chunks", test_combinations)
+@pytest.mark.timing
+def test_xarray_to_binary_flatten(tmp_path, max_size, chunks, time_file):
+    data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
+    data = data.chunk(chunks)
+    file_path = tmp_path / "test_xarray_to_binary_flatten.bin"
+
+    profile_function(
+        create_and_write_flatten,
+        (file_path, data),
+        time_file,
+        print_args={"max_size": max_size, "chunks": chunks},
+    )
+
+
+def create_and_write_flatten_blocks(file_path, data: xr.DataArray):
+    with open(file_path, "w") as f:
+        for block in data.data.to_delayed():
+            block_data = block.compute()
+            block_data.astype(np.int32).tofile(f)
+
+
+@pytest.mark.parametrize("max_size,chunks", test_combinations)
+@pytest.mark.timing
+def test_xarray_to_binary_flatten_blocks(
+    tmp_path, max_size, chunks, time_file
+):
+    data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
+    data = data.chunk(chunks)
+    file_path = tmp_path / "test_xarray_to_binary_flatten.bin"
+
+    profile_function(
+        create_and_write_flatten_blocks,
+        (file_path, data),
+        time_file,
+        print_args={"max_size": max_size, "chunks": chunks},
+    )
+
+
 @pytest.mark.parametrize("max_size,chunks", test_combinations)
 @pytest.mark.memory
 @pytest.mark.skip("Memory tests take a long time to run")
-def test_xarray_to_text_extras_mem(tmp_path, max_size, chunks, memory_file):
+def test_xarray_to_text_jinja_mem(tmp_path, max_size, chunks, memory_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
-    file_path = tmp_path / "test_xarray_to_text_extras.disu"
+    file_path = tmp_path / "test_xarray_to_text_jinja.disu"
 
     mem_check_function(
-        create_and_write_extras,
+        create_and_write_jinja,
         (file_path, data),
         memory_file,
         print_args={"max_size": max_size, "chunks": chunks},
@@ -237,7 +281,9 @@ def test_xarray_to_text_extras_mem(tmp_path, max_size, chunks, memory_file):
 
     with open(file_path, "r") as f:
         output = f.readlines()
-        assert len(output) == 3
+        assert (
+            len(output) == 2 + max_size / chunks
+        )  # begin + end + lines of data
 
 
 @pytest.mark.parametrize("max_size,chunks", test_combinations)
@@ -285,13 +331,13 @@ def test_xarray_to_text_np_savetext_mem(
 @pytest.mark.parametrize("max_size,chunks", test_combinations)
 @pytest.mark.memory
 @pytest.mark.skip("Memory tests take a long time to run")
-def test_xarray_to_text_jinja_mem(tmp_path, max_size, chunks, memory_file):
+def test_xarray_to_text_extras_mem(tmp_path, max_size, chunks, memory_file):
     data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
     data = data.chunk(chunks)
-    file_path = tmp_path / "test_xarray_to_text_jinja.disu"
+    file_path = tmp_path / "test_xarray_to_text_extras.disu"
 
     mem_check_function(
-        create_and_write_jinja,
+        create_and_write_extras,
         (file_path, data),
         memory_file,
         print_args={"max_size": max_size, "chunks": chunks},
@@ -299,6 +345,22 @@ def test_xarray_to_text_jinja_mem(tmp_path, max_size, chunks, memory_file):
 
     with open(file_path, "r") as f:
         output = f.readlines()
-        assert (
-            len(output) == 2 + max_size / chunks
-        )  # begin + end + lines of data
+        assert len(output) == 3
+
+
+@pytest.mark.parametrize("max_size,chunks", test_combinations)
+@pytest.mark.memory
+# @pytest.mark.skip("Memory tests take a long time to run")
+def test_xarray_to_binary_flatten_blocks_mem(
+    tmp_path, max_size, chunks, memory_file
+):
+    data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
+    data = data.chunk(chunks)
+    file_path = tmp_path / "test_xarray_to_binary_flatten.bin"
+
+    mem_check_function(
+        create_and_write_flatten_blocks,
+        (file_path, data),
+        memory_file,
+        print_args={"max_size": max_size, "chunks": chunks},
+    )

From e4b178bce8f96719d071454d9e5d1f941a0cf417 Mon Sep 17 00:00:00 2001
From: Marnix <marnix.kraus@deltares.nl>
Date: Wed, 8 Jan 2025 11:59:23 +0100
Subject: [PATCH 12/12] Add netcdf writing test

---
 test/test_xarray_io.py | 19 +++++++++++++++++++
 1 file changed, 19 insertions(+)

diff --git a/test/test_xarray_io.py b/test/test_xarray_io.py
index 6da7b33..4515fad 100644
--- a/test/test_xarray_io.py
+++ b/test/test_xarray_io.py
@@ -264,6 +264,25 @@ def test_xarray_to_binary_flatten_blocks(
     )
 
 
+def create_and_write_netcdf(file_path, data: xr.DataArray):
+    data.to_netcdf(file_path, format="NETCDF4", engine="netcdf4")
+
+
+@pytest.mark.parametrize("max_size,chunks", test_combinations)
+@pytest.mark.timing
+def test_xarray_to_binary_netcdf(tmp_path, max_size, chunks, time_file):
+    data = xr.DataArray(da.arange(0, max_size, 1), dims="x")
+    data = data.chunk(chunks)
+    file_path = tmp_path / "test_xarray_to_binary_netcdf.nc"
+
+    profile_function(
+        create_and_write_netcdf,
+        (file_path, data),
+        time_file,
+        print_args={"max_size": max_size, "chunks": chunks},
+    )
+
+
 @pytest.mark.parametrize("max_size,chunks", test_combinations)
 @pytest.mark.memory
 @pytest.mark.skip("Memory tests take a long time to run")