Hello community, here is the log from the commit of package python-datashader for openSUSE:Factory checked in at 2018-06-13 15:38:07 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Comparing /work/SRC/openSUSE:Factory/python-datashader (Old) and /work/SRC/openSUSE:Factory/.python-datashader.new (New) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "python-datashader" Wed Jun 13 15:38:07 2018 rev:2 rq:615177 version:0.6.5 Changes: -------- --- /work/SRC/openSUSE:Factory/python-datashader/python-datashader.changes 2018-06-03 12:33:51.989327091 +0200 +++ /work/SRC/openSUSE:Factory/.python-datashader.new/python-datashader.changes 2018-06-13 15:38:36.130300752 +0200 @@ -1,0 +2,5 @@ +Thu Jun 7 20:30:20 UTC 2018 - [email protected] + +- Fix some grammar issues. + +------------------------------------------------------------------- ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Other differences: ------------------ ++++++ python-datashader.spec ++++++ --- /var/tmp/diff_new_pack.rl8KZg/_old 2018-06-13 15:38:37.614246143 +0200 +++ /var/tmp/diff_new_pack.rl8KZg/_new 2018-06-13 15:38:37.618245996 +0200 @@ -13,6 +13,7 @@ # published by the Open Source Initiative. # Please submit bugfixes or comments via http://bugs.opensuse.org/ +# %{?!python_module:%define python_module() python-%{**} python3-%{**}} @@ -24,10 +25,10 @@ Name: python-datashader Version: 0.6.5 Release: 0 -License: BSD-3-Clause Summary: Data visualization toolchain based on aggregating into a grid -Url: http://github.com/bokeh/datashader +License: BSD-3-Clause Group: Development/Languages/Python +Url: http://github.com/bokeh/datashader Source: https://github.com/bokeh/datashader/archive/%{version}.tar.gz BuildRequires: %{python_module devel} BuildRequires: %{python_module setuptools} @@ -40,8 +41,8 @@ BuildRequires: %{python_module PyYAML} BuildRequires: %{python_module bokeh} BuildRequires: %{python_module colorcet} -BuildRequires: %{python_module dask} BuildRequires: %{python_module dask-dataframe} +BuildRequires: %{python_module dask} BuildRequires: %{python_module fastparquet} BuildRequires: %{python_module numba >= 0.24.0} BuildRequires: %{python_module numpy >= 1.7} @@ -80,14 +81,14 @@ transforming incoming data into an onscreen or printed image, with parameters that can be specified beforehand that affect the final result. While this approach works for small collections of data that -can be viewed in their entirety, for large datasets the visualization +can be viewed in their entirety, the visualization for large datasets is often the only way to understand what the data consists of, and there is no objective way to set the parameters to reveal this data. The datashader library breaks up the rendering pipeline into a series of stages where user-defined computations can be performed, allowing the visualization to adapt to and reveal the underlying properties of -the dataset. I.e., the datashader pipeline allows computation *on +the dataset, i.e. the datashader pipeline allows computation *on the visualization*, not just on the dataset, allowing it to do automatic ranging and scaling that takes the current visualization constraints into account. For instance, where a traditional system
