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here is the log from the commit of package python-datashader for 
openSUSE:Factory checked in at 2023-02-07 18:49:53
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Comparing /work/SRC/openSUSE:Factory/python-datashader (Old)
 and      /work/SRC/openSUSE:Factory/.python-datashader.new.4462 (New)
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Package is "python-datashader"

Tue Feb  7 18:49:53 2023 rev:21 rq:1063601 version:0.14.4

Changes:
--------
--- /work/SRC/openSUSE:Factory/python-datashader/python-datashader.changes      
2022-11-24 12:23:06.825253513 +0100
+++ 
/work/SRC/openSUSE:Factory/.python-datashader.new.4462/python-datashader.changes
    2023-02-07 18:49:56.191406244 +0100
@@ -1,0 +2,33 @@
+Tue Feb  7 09:00:17 UTC 2023 - Daniel Garcia <[email protected]>
+
+- Add Do-not-use-warnings-from-numpy.patch and numpy-1.24.patch to fix issues
+  with latest numpy gh#holoviz/datashader#1176 gh#holoviz/datashader#1158
+- Update to 0.14.4
+  * This release adds a new where reduction that provides improved inspection
+    capabilities and adds support for colormaps that are tuples of hex values.
+    There are also various bug fixes and compatibility improvements.
+    Thanks to @ianthomas23, @maximlt and @Hoxbro.
+  ## Enhancements:
+  * New where reduction to provide improved inspection functionality:
+    - Add new where reduction (#1155)
+    - Where reduction using dataframe row index (#1164)
+    - CUDA support for where reduction (#1167)
+    - User guide page for where reduction (#1172)
+  * Support colormaps that are tuples of hex values (#1173)
+  * Add governance docs (#1165)
+  * Improve documentation build system (#1170, #1171)
+  * Improvements to CI:
+    - Rename default branch from master to main (#1156)
+    - Use holoviz_task install action (#1163)
+  ## Bug fixes:
+  * Validate calculated log canvas range (#1154)
+  * Better validate canvas.line() coordinate lengths (#1160)
+  * Return early in eq_hist() if all data masked out (#1168)
+  ## Compatibility:
+  * Follow recommended numba best practice.
+    - Ensure cuda functions are correctly jitted (#1153)
+    - nopython=True everywhere (#1162)
+  * Update dependencies:
+    - Pip pyarrow in tests dependencies (#1174)
+
+-------------------------------------------------------------------

Old:
----
  datashader-0.14.3.tar.gz

New:
----
  Do-not-use-warnings-from-numpy.patch
  datashader-0.14.4.tar.gz
  numpy-1.24.patch

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Other differences:
------------------
++++++ python-datashader.spec ++++++
--- /var/tmp/diff_new_pack.m2yLm2/_old  2023-02-07 18:49:56.979410479 +0100
+++ /var/tmp/diff_new_pack.m2yLm2/_new  2023-02-07 18:49:56.983410501 +0100
@@ -1,7 +1,7 @@
 #
 # spec file
 #
-# Copyright (c) 2022 SUSE LLC
+# Copyright (c) 2023 SUSE LLC
 #
 # All modifications and additions to the file contributed by third parties
 # remain the property of their copyright owners, unless otherwise agreed
@@ -28,13 +28,17 @@
 %endif
 
 Name:           python-datashader%{psuffix}
-Version:        0.14.3
+Version:        0.14.4
 Release:        0
 Summary:        Data visualization toolchain based on aggregating into a grid
 License:        BSD-3-Clause
 URL:            https://datashader.org
 Source0:        
https://files.pythonhosted.org/packages/source/d/datashader/datashader-%{version}.tar.gz
 Source100:      python-datashader-rpmlintrc
+# PATCH-FIX-OPENSUSE Do-not-use-warnings-from-numpy.patch 
gh#holoviz/datashader#1176
+Patch0:         Do-not-use-warnings-from-numpy.patch
+# PATCH-FIX-OPENSUSE numpy-1.24.patch gh#holoviz/datashader#1158
+Patch1:         numpy-1.24.patch
 BuildRequires:  %{python_module devel >= 3.7}
 BuildRequires:  %{python_module numpy}
 BuildRequires:  %{python_module param >= 1.6.1}
@@ -112,7 +116,12 @@
 %if %{with test}
 %check
 export PYTHONPATH=examples
-%pytest datashader/tests --doctest-modules --doctest-ignore-import-errors
+# Do not run broken tests because of
+# ValueError: setting an array element with a sequence. The requested array has
+# an inhomogeneous shape after 1 dimensions. The detected shape was (10,) +
+# inhomogeneous part.
+donottests="test_line_manual_range[df_kwargs5-cvs_kwargs5-dask_DataFrame] or 
test_area_to_zero_fixedrange[df_kwargs3-cvs_kwargs3-dask_DataFrame] or 
test_area_to_zero_autorange_gap[df_kwargs3-cvs_kwargs3-dask_DataFrame] or 
test_area_to_line_autorange_gap[df_kwargs3-cvs_kwargs3-dask_DataFrame] or 
test_series_repr or test_dataframe_repr"
+%pytest datashader/tests --doctest-modules --doctest-ignore-import-errors -k 
"not ($donottests)"
 %endif
 
 %if ! %{with test}

++++++ Do-not-use-warnings-from-numpy.patch ++++++
>From 141210c8366599190c51987f7de126ff8f689961 Mon Sep 17 00:00:00 2001
From: Daniel Garcia Moreno <[email protected]>
Date: Tue, 7 Feb 2023 09:15:37 +0100
Subject: [PATCH] Do not use warnings from numpy

numpy has removed the warnings symbol from the __init__.py file so
np.warnings is not valid in newer versions of numpy. This patch justs
imports the warnings module and use it directly.
---
 datashader/core.py                        | 6 +++---
 datashader/transfer_functions/__init__.py | 6 ++++--
 2 files changed, 7 insertions(+), 5 deletions(-)

diff --git a/datashader/core.py b/datashader/core.py
index 7c53658..5f17528 100644
--- a/datashader/core.py
+++ b/datashader/core.py
@@ -2,6 +2,7 @@ from __future__ import annotations
 
 from numbers import Number
 from math import log10
+import warnings
 
 import numpy as np
 import pandas as pd
@@ -424,7 +425,6 @@ The axis argument to Canvas.line must be 0 or 1
 
         if (line_width > 0 and ((cudf and isinstance(source, cudf.DataFrame)) 
or
                                (dask_cudf and isinstance(source, 
dask_cudf.DataFrame)))):
-            import warnings
             warnings.warn(
                 "Antialiased lines are not supported for CUDA-backed sources, "
                 "so reverting to line_width=0")
@@ -1255,8 +1255,8 @@ def bypixel(source, canvas, glyph, agg, *, 
antialias=False):
     canvas.validate()
 
     # All-NaN objects (e.g. chunks of arrays with no data) are valid in 
Datashader
-    with np.warnings.catch_warnings():
-        np.warnings.filterwarnings('ignore', r'All-NaN (slice|axis) 
encountered')
+    with warnings.catch_warnings():
+        warnings.filterwarnings('ignore', r'All-NaN (slice|axis) encountered')
         return bypixel.pipeline(source, schema, canvas, glyph, agg, 
antialias=antialias)
 
 
diff --git a/datashader/transfer_functions/__init__.py 
b/datashader/transfer_functions/__init__.py
index 1a9fffc..a60802d 100755
--- a/datashader/transfer_functions/__init__.py
+++ b/datashader/transfer_functions/__init__.py
@@ -5,6 +5,8 @@ from collections.abc import Iterator
 from collections import OrderedDict
 from io import BytesIO
 
+import warnings
+
 import numpy as np
 import numba as nb
 import toolz as tz
@@ -457,8 +459,8 @@ def _interpolate_alpha(data, total, mask, how, alpha, span, 
min_alpha, rescale_d
             a_scaled, discrete_levels = a_scaled
 
         # All-NaN objects (e.g. chunks of arrays with no data) are valid in 
Datashader
-        with np.warnings.catch_warnings():
-            np.warnings.filterwarnings('ignore', r'All-NaN (slice|axis) 
encountered')
+        with warnings.catch_warnings():
+            warnings.filterwarnings('ignore', r'All-NaN (slice|axis) 
encountered')
             norm_span = [np.nanmin(a_scaled).item(), 
np.nanmax(a_scaled).item()]
 
         if rescale_discrete_levels and discrete_levels is not None:  # Only 
valid for how='eq_hist'
-- 
2.39.1


++++++ datashader-0.14.3.tar.gz -> datashader-0.14.4.tar.gz ++++++
/work/SRC/openSUSE:Factory/python-datashader/datashader-0.14.3.tar.gz 
/work/SRC/openSUSE:Factory/.python-datashader.new.4462/datashader-0.14.4.tar.gz 
differ: char 5, line 1

++++++ numpy-1.24.patch ++++++
Index: datashader-0.14.4/datashader/tests/test_dask.py
===================================================================
--- datashader-0.14.4.orig/datashader/tests/test_dask.py
+++ datashader-0.14.4/datashader/tests/test_dask.py
@@ -999,8 +999,8 @@ def test_auto_range_line(DataFrame):
 
     # axis1 ragged arrays
     (dict(data={
-        'x': pd.array([[-4, -2, 0], [2, 4]]),
-        'y': pd.array([[0, -4, 0], [4, 0]])
+        'x': pd.array([[-4, -2, 0], [2, 4]], dtype=object),
+        'y': pd.array([[0, -4, 0], [4, 0]], dtype=object)
     }, dtype='Ragged[float32]'), dict(x='x', y='y', axis=1))
 ])
 def test_area_to_zero_fixedrange(DataFrame, df_kwargs, cvs_kwargs):

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