From 0f4a7687d55e785ec1bcb28f3b7a75a0f23b3da8 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Tue, 4 Nov 2025 07:46:57 -0500 Subject: [PATCH 01/41] remove pvlib restriction --- setup.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.py b/setup.py index 441b16c0..f0363562 100755 --- a/setup.py +++ b/setup.py @@ -51,7 +51,7 @@ "h5py >= 3.7.0", "plotly>=4.0.0", "xgboost >= 1.6.0", - "pvlib >= 0.11.0, <0.12.0", + "pvlib", "scikit-learn >= 1.1.3, <1.6.0", "arch >= 5.0", "filterpy >= 1.4.2", From bf74f613f9eab0f6f4b25ce39b58adbab2151abc Mon Sep 17 00:00:00 2001 From: martin-springer Date: Tue, 4 Nov 2025 07:58:19 -0500 Subject: [PATCH 02/41] run tests with pvlib 0.13.1 --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 387589a4..c3ee7a8d 100644 --- a/requirements.txt +++ b/requirements.txt @@ -14,7 +14,7 @@ pandas==2.2.2 patsy==0.5.6 Pillow==10.4.0 plotly==5.23.0 -pvlib==0.11.0 +pvlib==0.13.1 pyparsing==3.1.2 python-dateutil==2.9.0 pytz==2024.1 From b76a855f3c4209b5b6ff2e98a677ecee36414fb5 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 09:13:14 -0500 Subject: [PATCH 03/41] re-run TA NSRDB notebook --- docs/TrendAnalysis_example_NSRDB.ipynb | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/TrendAnalysis_example_NSRDB.ipynb b/docs/TrendAnalysis_example_NSRDB.ipynb index 6c9f6b7d..b7e0677f 100644 --- a/docs/TrendAnalysis_example_NSRDB.ipynb +++ b/docs/TrendAnalysis_example_NSRDB.ipynb @@ -143,7 +143,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -276,7 +276,7 @@ "output_type": "stream", "text": [ "-0.394\n", - "[-0.939 0.102]\n" + "[-0.984 0.102]\n" ] } ], @@ -293,7 +293,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -314,7 +314,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "rdtools3-nb", + "display_name": "rdtools_313", "language": "python", "name": "python3" }, @@ -328,7 +328,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.7" + "version": "3.13.11" } }, "nbformat": 4, From 2427d6da20e0203b11890efc629af14776176737 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 09:16:40 -0500 Subject: [PATCH 04/41] update changelog --- docs/sphinx/source/changelog/pending.rst | 4 ++++ 1 file changed, 4 insertions(+) create mode 100644 docs/sphinx/source/changelog/pending.rst diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst new file mode 100644 index 00000000..79b5a712 --- /dev/null +++ b/docs/sphinx/source/changelog/pending.rst @@ -0,0 +1,4 @@ +Requirements +------------ +* Removed pvlib version restrictions in setup.py. Previously "pvlib >= 0.11.0, <0.12.0", now "pvlib". +* Updated pvlib version in requirements.txt from 0.11.0 to 0.13.1 From 2b68e14353b67164638174c072210edadead2d08 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 09:25:22 -0500 Subject: [PATCH 05/41] restrict pandas to <3.0.0 --- setup.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.py b/setup.py index f0363562..3d1aa6a6 100755 --- a/setup.py +++ b/setup.py @@ -45,7 +45,7 @@ INSTALL_REQUIRES = [ "matplotlib >= 3.5.3", "numpy >= 1.22.4", - "pandas >= 1.4.4", + "pandas >= 1.4.4, <3.0.0", "statsmodels >= 0.13.5", "scipy >= 1.8.1", "h5py >= 3.7.0", From bf00799b0098e12f1a4101b4aeb73202cad7067e Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 09:26:26 -0500 Subject: [PATCH 06/41] add nbval workflow filterwarnings --- setup.cfg | 1 + 1 file changed, 1 insertion(+) diff --git a/setup.cfg b/setup.cfg index 36500c52..986e70ef 100644 --- a/setup.cfg +++ b/setup.cfg @@ -26,3 +26,4 @@ addopts = --verbose # https://docs.python.org/3/library/warnings.html#the-warnings-filter filterwarnings = ignore:The .* module is currently experimental:UserWarning:rdtools + ignore:The \(fspath. py\.path\.local\) argument to IPyNbFile is deprecated From f7140c97a24eb3632029c2a9de480493bd0c5259 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 09:26:32 -0500 Subject: [PATCH 07/41] update changelog --- docs/sphinx/source/changelog/pending.rst | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index 79b5a712..e27bbfe3 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -2,3 +2,9 @@ Requirements ------------ * Removed pvlib version restrictions in setup.py. Previously "pvlib >= 0.11.0, <0.12.0", now "pvlib". * Updated pvlib version in requirements.txt from 0.11.0 to 0.13.1 +* Added pandas upper version restriction in setup.py. Now "pandas >= 1.4.4, <3.0.0". + + +Warnings +-------- +* Added filter to ignore deprecation warning related to IPyNbFile in setup.cfg. \ No newline at end of file From e9cbd5004aa0b656a9e58802873445f246a65d86 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 09:38:57 -0500 Subject: [PATCH 08/41] try limiting numpy version for eager tests --- setup.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/setup.py b/setup.py index 3d1aa6a6..794523cc 100755 --- a/setup.py +++ b/setup.py @@ -44,7 +44,7 @@ INSTALL_REQUIRES = [ "matplotlib >= 3.5.3", - "numpy >= 1.22.4", + "numpy >= 1.22.4, <2.3.0", "pandas >= 1.4.4, <3.0.0", "statsmodels >= 0.13.5", "scipy >= 1.8.1", @@ -80,10 +80,10 @@ "Intended Audience :: Science/Research", "Programming Language :: Python", "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", "Topic :: Scientific/Engineering", ] From bd94a2ee133129a905aa940c9326a86f2ee52212 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 09:39:10 -0500 Subject: [PATCH 09/41] update python versions in test matrix --- .github/workflows/pytest.yaml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/pytest.yaml b/.github/workflows/pytest.yaml index fc277b09..77d79318 100644 --- a/.github/workflows/pytest.yaml +++ b/.github/workflows/pytest.yaml @@ -14,21 +14,21 @@ jobs: runs-on: ubuntu-latest strategy: matrix: - python-version: ["3.9", "3.10", "3.11", "3.12"] + python-version: ["3.10", "3.11", "3.12", "3.13"] env: [ '-r requirements.txt .[test]', '-r requirements-min.txt .[test]', '--upgrade --upgrade-strategy=eager .[test]' ] exclude: - - python-version: "3.9" - env: "-r requirements.txt .[test]" - python-version: "3.10" env: '-r requirements-min.txt .[test]' - python-version: "3.11" env: '-r requirements-min.txt .[test]' - python-version: "3.12" env: '-r requirements-min.txt .[test]' + - python-version: "3.13" + env: '-r requirements-min.txt .[test]' fail-fast: false steps: From fdd1f3dc72735647ef31c00798d3458a402fc8a4 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 09:49:03 -0500 Subject: [PATCH 10/41] increase pandas requirement to 2.2.3 for python 3.13 compatibility --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index c3ee7a8d..45274a17 100644 --- a/requirements.txt +++ b/requirements.txt @@ -10,7 +10,7 @@ kiwisolver==1.4.5 matplotlib==3.9.2 numpy==2.1.1 packaging==24.1 -pandas==2.2.2 +pandas==2.2.3 patsy==0.5.6 Pillow==10.4.0 plotly==5.23.0 From e8b42f0f2120987c56f9b4a4688e2ea32ab5aaac Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 09:54:38 -0500 Subject: [PATCH 11/41] increase scipy version for py 3.13 compatibility --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 45274a17..5db99752 100644 --- a/requirements.txt +++ b/requirements.txt @@ -23,7 +23,7 @@ filterpy==1.4.5 requests==2.32.3 retrying==1.3.4 scikit-learn==1.5.1 -scipy==1.13.1 +scipy==1.14.1 setuptools-scm==8.1.0 six==1.16.0 statsmodels==0.14.2 From 6b8440a9f1dd1e35391b4b7c0067f602a1cffa56 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 09:55:01 -0500 Subject: [PATCH 12/41] update changelog --- docs/sphinx/source/changelog/pending.rst | 3 +++ 1 file changed, 3 insertions(+) diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index e27bbfe3..7737b8b6 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -3,6 +3,9 @@ Requirements * Removed pvlib version restrictions in setup.py. Previously "pvlib >= 0.11.0, <0.12.0", now "pvlib". * Updated pvlib version in requirements.txt from 0.11.0 to 0.13.1 * Added pandas upper version restriction in setup.py. Now "pandas >= 1.4.4, <3.0.0". +* Added numpy upper version restriction in setup.py. Now "numpy >= 1.22.4, <2.3.0". +* Updated pandas version in requirements.txt from 2.2.2 to 2.2.3 for python 3.13 compativility. +* Updated scipy version in requirements.txt from 1.13.1 to 1.14.1 for python 3.13 compatibility. Warnings From 97efaa4522f8737694b2cb2688f10601071e5caf Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:01:17 -0500 Subject: [PATCH 13/41] increase h5py requirement for py 3.13 compatiblity --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 5db99752..44ea58df 100644 --- a/requirements.txt +++ b/requirements.txt @@ -3,7 +3,7 @@ certifi==2024.7.4 chardet==5.2.0 cycler==0.12.1 fonttools==4.53.1 -h5py==3.11.0 +h5py==3.12.0 idna==3.7 joblib==1.4.2 kiwisolver==1.4.5 From 11f9b4c725e38f02a365616f6b981ec31f97830b Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:01:44 -0500 Subject: [PATCH 14/41] update changelog --- docs/sphinx/source/changelog/pending.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index 7737b8b6..dbe0ba30 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -6,6 +6,7 @@ Requirements * Added numpy upper version restriction in setup.py. Now "numpy >= 1.22.4, <2.3.0". * Updated pandas version in requirements.txt from 2.2.2 to 2.2.3 for python 3.13 compativility. * Updated scipy version in requirements.txt from 1.13.1 to 1.14.1 for python 3.13 compatibility. +* Updated h5py version in requirements.txt from 3.11.0 to 3.12.0 for python 3.13 compatibility. Warnings From c2dc17ebe6f040a4bb472a3f58eb47e4f636286c Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:06:10 -0500 Subject: [PATCH 15/41] increase scikit-learn version for py 3.13 compatibility --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 44ea58df..f3e1987b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -22,7 +22,7 @@ arch==7.0.0 filterpy==1.4.5 requests==2.32.3 retrying==1.3.4 -scikit-learn==1.5.1 +scikit-learn==1.6.0 scipy==1.14.1 setuptools-scm==8.1.0 six==1.16.0 From bdd823062f24cb1d799f5c85ba6d7e868d8258eb Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:06:43 -0500 Subject: [PATCH 16/41] update changelog --- docs/sphinx/source/changelog/pending.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index dbe0ba30..b0074cd9 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -7,6 +7,7 @@ Requirements * Updated pandas version in requirements.txt from 2.2.2 to 2.2.3 for python 3.13 compativility. * Updated scipy version in requirements.txt from 1.13.1 to 1.14.1 for python 3.13 compatibility. * Updated h5py version in requirements.txt from 3.11.0 to 3.12.0 for python 3.13 compatibility. +* Updated scikit-learn version in requirements.txt from 1.5.1 to 1.6.0 for python 3.13 compatibility. Warnings From febf3c30154ce57336d85345fea02683fa6ab646 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:07:45 -0500 Subject: [PATCH 17/41] update plotly for py 3.13 compatibility --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index f3e1987b..31d15f28 100644 --- a/requirements.txt +++ b/requirements.txt @@ -13,7 +13,7 @@ packaging==24.1 pandas==2.2.3 patsy==0.5.6 Pillow==10.4.0 -plotly==5.23.0 +plotly==6.1.1 pvlib==0.13.1 pyparsing==3.1.2 python-dateutil==2.9.0 From 177ee05866d74433ac972996fd5cd6463c2abba9 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:09:40 -0500 Subject: [PATCH 18/41] update setuptools-scm for py 3.13 support --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 31d15f28..4636474b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -24,7 +24,7 @@ requests==2.32.3 retrying==1.3.4 scikit-learn==1.6.0 scipy==1.14.1 -setuptools-scm==8.1.0 +setuptools-scm==9.2.2 six==1.16.0 statsmodels==0.14.2 threadpoolctl==3.5.0 From 747e2a72805d6d5b68df45fa5112ee16399d74c0 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:10:22 -0500 Subject: [PATCH 19/41] update six to support py 3.13 --- docs/sphinx/source/changelog/pending.rst | 2 ++ requirements.txt | 2 +- 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index b0074cd9..5a459c65 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -8,6 +8,8 @@ Requirements * Updated scipy version in requirements.txt from 1.13.1 to 1.14.1 for python 3.13 compatibility. * Updated h5py version in requirements.txt from 3.11.0 to 3.12.0 for python 3.13 compatibility. * Updated scikit-learn version in requirements.txt from 1.5.1 to 1.6.0 for python 3.13 compatibility. +* Updated plotly version in requirements.txt from 5.23.0 to 6.1.1 for python 3.13 compatibility. +* Updated setuptools-scm version in requirements.txt from 8.1.0 to 9.2.2 for python 3.13 compatibility. Warnings diff --git a/requirements.txt b/requirements.txt index 4636474b..c7d46be5 100644 --- a/requirements.txt +++ b/requirements.txt @@ -25,7 +25,7 @@ retrying==1.3.4 scikit-learn==1.6.0 scipy==1.14.1 setuptools-scm==9.2.2 -six==1.16.0 +six==1.17.0 statsmodels==0.14.2 threadpoolctl==3.5.0 tomli==2.0.1 From 366f2575af2137918846f0519efd358d82182050 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:10:58 -0500 Subject: [PATCH 20/41] update statsmodels for py 3.13 support --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index c7d46be5..9517a3ec 100644 --- a/requirements.txt +++ b/requirements.txt @@ -26,7 +26,7 @@ scikit-learn==1.6.0 scipy==1.14.1 setuptools-scm==9.2.2 six==1.17.0 -statsmodels==0.14.2 +statsmodels==0.14.6 threadpoolctl==3.5.0 tomli==2.0.1 typing_extensions==4.12.2 From d573f7950a7b2a72e5a2819d8c70a1c642b8c61b Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:11:29 -0500 Subject: [PATCH 21/41] update threadpoolctl for py 3.13 support --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 9517a3ec..7281a0b5 100644 --- a/requirements.txt +++ b/requirements.txt @@ -27,7 +27,7 @@ scipy==1.14.1 setuptools-scm==9.2.2 six==1.17.0 statsmodels==0.14.6 -threadpoolctl==3.5.0 +threadpoolctl==3.6.0 tomli==2.0.1 typing_extensions==4.12.2 urllib3==2.2.2 From 0305a0bbca922ccf17a80032f261cd7f9c3b2202 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:12:31 -0500 Subject: [PATCH 22/41] update tomli for py 3.13 support --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 7281a0b5..39a5d665 100644 --- a/requirements.txt +++ b/requirements.txt @@ -28,7 +28,7 @@ setuptools-scm==9.2.2 six==1.17.0 statsmodels==0.14.6 threadpoolctl==3.6.0 -tomli==2.0.1 +tomli==2.0.2 typing_extensions==4.12.2 urllib3==2.2.2 xgboost==2.1.1 From 18bd82dec3df40b7fff3038ad89f1b8708e9ec0e Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:12:51 -0500 Subject: [PATCH 23/41] update typing_extensions for py 3.13 --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 39a5d665..d320caa8 100644 --- a/requirements.txt +++ b/requirements.txt @@ -29,7 +29,7 @@ six==1.17.0 statsmodels==0.14.6 threadpoolctl==3.6.0 tomli==2.0.2 -typing_extensions==4.12.2 +typing_extensions==4.15.0 urllib3==2.2.2 xgboost==2.1.1 From 1ed42ba742a1a966180b2b3fa3400978c8ef2018 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:13:28 -0500 Subject: [PATCH 24/41] update urllib3 for py 3.13 --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index d320caa8..0838c2a9 100644 --- a/requirements.txt +++ b/requirements.txt @@ -30,6 +30,6 @@ statsmodels==0.14.6 threadpoolctl==3.6.0 tomli==2.0.2 typing_extensions==4.15.0 -urllib3==2.2.2 +urllib3==2.4.0 xgboost==2.1.1 From f86813c340d3085ac2e43fafe2059e1b4f83e3c8 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:14:35 -0500 Subject: [PATCH 25/41] update xgboost for py 3.13 --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 0838c2a9..6fba2dae 100644 --- a/requirements.txt +++ b/requirements.txt @@ -31,5 +31,5 @@ threadpoolctl==3.6.0 tomli==2.0.2 typing_extensions==4.15.0 urllib3==2.4.0 -xgboost==2.1.1 +xgboost==3.1.3 From 4d0c25bb0d918703e8d25fb1b82eb3b17a582a0b Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:16:07 -0500 Subject: [PATCH 26/41] update fonttools for py 3.13 --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 6fba2dae..9ad80c69 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,7 +2,7 @@ cached-property==1.5.2 certifi==2024.7.4 chardet==5.2.0 cycler==0.12.1 -fonttools==4.53.1 +fonttools==4.58.4 h5py==3.12.0 idna==3.7 joblib==1.4.2 From 7d2256121a2aea7024295297e3e75597b649d026 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:16:21 -0500 Subject: [PATCH 27/41] update idna for py 3.13 support --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 9ad80c69..6dfa489d 100644 --- a/requirements.txt +++ b/requirements.txt @@ -4,7 +4,7 @@ chardet==5.2.0 cycler==0.12.1 fonttools==4.58.4 h5py==3.12.0 -idna==3.7 +idna==3.8 joblib==1.4.2 kiwisolver==1.4.5 matplotlib==3.9.2 From 3c050637e4649a1f2143493d0707fee402a802e9 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:16:56 -0500 Subject: [PATCH 28/41] update joblib for py 3.13 --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 6dfa489d..ef6ec4a4 100644 --- a/requirements.txt +++ b/requirements.txt @@ -5,7 +5,7 @@ cycler==0.12.1 fonttools==4.58.4 h5py==3.12.0 idna==3.8 -joblib==1.4.2 +joblib==1.5.2 kiwisolver==1.4.5 matplotlib==3.9.2 numpy==2.1.1 From 5456eb0e2c4018699f76883e0857490d36f7ad8c Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:17:51 -0500 Subject: [PATCH 29/41] updated kiwisolver for py 3.13 --- docs/sphinx/source/changelog/pending.rst | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index 5a459c65..49afd4b0 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -10,6 +10,16 @@ Requirements * Updated scikit-learn version in requirements.txt from 1.5.1 to 1.6.0 for python 3.13 compatibility. * Updated plotly version in requirements.txt from 5.23.0 to 6.1.1 for python 3.13 compatibility. * Updated setuptools-scm version in requirements.txt from 8.1.0 to 9.2.2 for python 3.13 compatibility. +* Updated six version in requirements.txt from 1.16.0 to 1.17.0 for python 3.13 compatibility. +* Updated statsmodels version in requirements.txt from 0.14.2 to 0.14.6 for python 3.13 compatibility. +* Updated threadpoolctl version in requirements.txt from 3.5.0 to 3.6.0 for python 3.13 compatibility. +* Updated tomli version in requirements.txt from 2.0.1 to 2.0.2 for python 3.13 compatibility. +* Updated typing_extensions version in requirements.txt from 4.12.2 to 4.15.0 for python 3.13 compatibility. +* Updated urllib3 version in requirements.txt from 2.2.2 to 2.4.0 for python 3.13 compatibility. +* Updated xgboost version in requirements.txt from 2.1.1 to 3.1.3 for python 3.13 compatibility. +* Updated fonttools version in requirements.txt from 4.53.1 to 4.58.4 for python 3.13 compatibility. +* Updated idna version in requirements.txt from 3.7 to 3.8 for python 3.13 compatibility. +* Updated joblib version in requirements.txt from 1.4.2 to 1.5.2 for python 3.13 compatibility. Warnings From d0765c03a664c391151ca3148498201cdf932835 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:18:06 -0500 Subject: [PATCH 30/41] updated matplotlib for py 3.13 --- requirements.txt | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/requirements.txt b/requirements.txt index ef6ec4a4..9cb9f296 100644 --- a/requirements.txt +++ b/requirements.txt @@ -6,8 +6,8 @@ fonttools==4.58.4 h5py==3.12.0 idna==3.8 joblib==1.5.2 -kiwisolver==1.4.5 -matplotlib==3.9.2 +kiwisolver==1.4.6 +matplotlib==3.9.4 numpy==2.1.1 packaging==24.1 pandas==2.2.3 From 0599a427586d2c5314a6aa00565a49e7a8421018 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:19:15 -0500 Subject: [PATCH 31/41] update packaging for py 3.13 --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 9cb9f296..7ceb63f0 100644 --- a/requirements.txt +++ b/requirements.txt @@ -9,7 +9,7 @@ joblib==1.5.2 kiwisolver==1.4.6 matplotlib==3.9.4 numpy==2.1.1 -packaging==24.1 +packaging==26.0 pandas==2.2.3 patsy==0.5.6 Pillow==10.4.0 From 4be18fb9f093a48011fa3f618f5641572b223dde Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:19:54 -0500 Subject: [PATCH 32/41] update patsy for py 3.13 support --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 7ceb63f0..dc092a95 100644 --- a/requirements.txt +++ b/requirements.txt @@ -11,7 +11,7 @@ matplotlib==3.9.4 numpy==2.1.1 packaging==26.0 pandas==2.2.3 -patsy==0.5.6 +patsy==1.0.0 Pillow==10.4.0 plotly==6.1.1 pvlib==0.13.1 From 5458392651a6fe63eb0ed4008282a7a05096ecd3 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:20:20 -0500 Subject: [PATCH 33/41] update Pillow for py 3.13 --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index dc092a95..5156b407 100644 --- a/requirements.txt +++ b/requirements.txt @@ -12,7 +12,7 @@ numpy==2.1.1 packaging==26.0 pandas==2.2.3 patsy==1.0.0 -Pillow==10.4.0 +Pillow==11.0.0 plotly==6.1.1 pvlib==0.13.1 pyparsing==3.1.2 From b9b811d4778e08c172b6df5ab2a6e240eba08d63 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:21:43 -0500 Subject: [PATCH 34/41] update pyparsing for py 3.13 --- requirements.txt | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/requirements.txt b/requirements.txt index 5156b407..754aaa5d 100644 --- a/requirements.txt +++ b/requirements.txt @@ -14,8 +14,8 @@ pandas==2.2.3 patsy==1.0.0 Pillow==11.0.0 plotly==6.1.1 -pvlib==0.13.1 -pyparsing==3.1.2 +pvlib==0.14.0 +pyparsing==3.2.0 python-dateutil==2.9.0 pytz==2024.1 arch==7.0.0 From b7f14b91fa8384978f058a6a4e0b0170f3562c02 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:22:37 -0500 Subject: [PATCH 35/41] update pytz for py 3.13 --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 754aaa5d..d3d78fd1 100644 --- a/requirements.txt +++ b/requirements.txt @@ -17,7 +17,7 @@ plotly==6.1.1 pvlib==0.14.0 pyparsing==3.2.0 python-dateutil==2.9.0 -pytz==2024.1 +pytz==2025.2 arch==7.0.0 filterpy==1.4.5 requests==2.32.3 From 23aec01bb4bf97a53854d9469ed6223b316b926b Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:25:47 -0500 Subject: [PATCH 36/41] update changelog --- docs/sphinx/source/changelog/pending.rst | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index 49afd4b0..758eb95d 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -1,7 +1,7 @@ Requirements ------------ * Removed pvlib version restrictions in setup.py. Previously "pvlib >= 0.11.0, <0.12.0", now "pvlib". -* Updated pvlib version in requirements.txt from 0.11.0 to 0.13.1 +* Updated pvlib version in requirements.txt from 0.11.0 to 0.14.0 * Added pandas upper version restriction in setup.py. Now "pandas >= 1.4.4, <3.0.0". * Added numpy upper version restriction in setup.py. Now "numpy >= 1.22.4, <2.3.0". * Updated pandas version in requirements.txt from 2.2.2 to 2.2.3 for python 3.13 compativility. @@ -20,6 +20,13 @@ Requirements * Updated fonttools version in requirements.txt from 4.53.1 to 4.58.4 for python 3.13 compatibility. * Updated idna version in requirements.txt from 3.7 to 3.8 for python 3.13 compatibility. * Updated joblib version in requirements.txt from 1.4.2 to 1.5.2 for python 3.13 compatibility. +* Updated kiwisolver version in requirements.txt from 1.4.5 to 1.4.6 for python 3.13 compatibility. +* Updated matplotlib version in requirements.txt from 3.9.2 to 3.9.4 for python 3.13 compatibility. +* Updated packaging version in requirements.txt from 24.1 to 26.0 for python 3.13 compatibility. +* Updated patsy version in requirements.txt from 0.5.6 to 1.0.0 for python 3.13 compatibility. +* Updated Pillow version in requirements.txt from 10.4.0 to 11.0.0 for python 3.13 compatibility. +* Updated pyparsing version in requirements.txt from 3.1.2 to 3.2.0 for python 3.13 compatibility. +* Updated pytz version in requirements.txt from 2024.1 to 2025.2 for python 3.13 compatibility. Warnings From 8679ddc4eaac2675c4fa8161ecb7296de6ce5d57 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:27:55 -0500 Subject: [PATCH 37/41] try new scikit-learn version --- requirements.txt | 2 +- setup.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/requirements.txt b/requirements.txt index d3d78fd1..28d6d556 100644 --- a/requirements.txt +++ b/requirements.txt @@ -22,7 +22,7 @@ arch==7.0.0 filterpy==1.4.5 requests==2.32.3 retrying==1.3.4 -scikit-learn==1.6.0 +scikit-learn==1.8.0 scipy==1.14.1 setuptools-scm==9.2.2 six==1.17.0 diff --git a/setup.py b/setup.py index 794523cc..8ee58b75 100755 --- a/setup.py +++ b/setup.py @@ -52,7 +52,7 @@ "plotly>=4.0.0", "xgboost >= 1.6.0", "pvlib", - "scikit-learn >= 1.1.3, <1.6.0", + "scikit-learn", "arch >= 5.0", "filterpy >= 1.4.2", ] From dc9f2099b57844f8151f820bdec93dea77c95ce0 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:29:26 -0500 Subject: [PATCH 38/41] scikit-learn version 1.7.2 for py 3.13 and xgboost compatibility --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 28d6d556..b1771191 100644 --- a/requirements.txt +++ b/requirements.txt @@ -22,7 +22,7 @@ arch==7.0.0 filterpy==1.4.5 requests==2.32.3 retrying==1.3.4 -scikit-learn==1.8.0 +scikit-learn==1.7.2 scipy==1.14.1 setuptools-scm==9.2.2 six==1.17.0 From cc11b5f8f4b7bd9988af041fe31b8c4fe2adc5cd Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:29:51 -0500 Subject: [PATCH 39/41] update changelog --- docs/sphinx/source/changelog/pending.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index 758eb95d..d2c5ff0c 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -7,7 +7,7 @@ Requirements * Updated pandas version in requirements.txt from 2.2.2 to 2.2.3 for python 3.13 compativility. * Updated scipy version in requirements.txt from 1.13.1 to 1.14.1 for python 3.13 compatibility. * Updated h5py version in requirements.txt from 3.11.0 to 3.12.0 for python 3.13 compatibility. -* Updated scikit-learn version in requirements.txt from 1.5.1 to 1.6.0 for python 3.13 compatibility. +* Updated scikit-learn version in requirements.txt from 1.5.1 to 1.7.2 for python 3.13 and xgboost compatibility. * Updated plotly version in requirements.txt from 5.23.0 to 6.1.1 for python 3.13 compatibility. * Updated setuptools-scm version in requirements.txt from 8.1.0 to 9.2.2 for python 3.13 compatibility. * Updated six version in requirements.txt from 1.16.0 to 1.17.0 for python 3.13 compatibility. From b56bd287e3dcce6cab95a00c2bd284249c34c025 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:40:31 -0500 Subject: [PATCH 40/41] bump urllib3 to satisfy dependabot --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index b1771191..1ed3dc65 100644 --- a/requirements.txt +++ b/requirements.txt @@ -30,6 +30,6 @@ statsmodels==0.14.6 threadpoolctl==3.6.0 tomli==2.0.2 typing_extensions==4.15.0 -urllib3==2.4.0 +urllib3==2.6.3 xgboost==3.1.3 From 8308d66295ad040a2d23d42649a58be04694b626 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 30 Jan 2026 10:41:17 -0500 Subject: [PATCH 41/41] update changelog --- docs/sphinx/source/changelog/pending.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index d2c5ff0c..ac91954f 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -15,7 +15,7 @@ Requirements * Updated threadpoolctl version in requirements.txt from 3.5.0 to 3.6.0 for python 3.13 compatibility. * Updated tomli version in requirements.txt from 2.0.1 to 2.0.2 for python 3.13 compatibility. * Updated typing_extensions version in requirements.txt from 4.12.2 to 4.15.0 for python 3.13 compatibility. -* Updated urllib3 version in requirements.txt from 2.2.2 to 2.4.0 for python 3.13 compatibility. +* Updated urllib3 version in requirements.txt from 2.2.2 to 2.6.3 for python 3.13 compatibility and to fix security issues. * Updated xgboost version in requirements.txt from 2.1.1 to 3.1.3 for python 3.13 compatibility. * Updated fonttools version in requirements.txt from 4.53.1 to 4.58.4 for python 3.13 compatibility. * Updated idna version in requirements.txt from 3.7 to 3.8 for python 3.13 compatibility.