Hello community,
here is the log from the commit of package python-metakernel for
openSUSE:Factory checked in at 2019-11-13 13:28:33
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Comparing /work/SRC/openSUSE:Factory/python-metakernel (Old)
and /work/SRC/openSUSE:Factory/.python-metakernel.new.2990 (New)
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "python-metakernel"
Wed Nov 13 13:28:33 2019 rev:5 rq:747920 version:0.24.3
Changes:
--------
--- /work/SRC/openSUSE:Factory/python-metakernel/python-metakernel.changes
2019-08-13 13:20:44.085426747 +0200
+++
/work/SRC/openSUSE:Factory/.python-metakernel.new.2990/python-metakernel.changes
2019-11-13 13:28:34.767713416 +0100
@@ -1,0 +2,7 @@
+Tue Nov 12 17:01:17 UTC 2019 - Todd R <[email protected]>
+
+- Update to 0.24.3
+ * Update setup.py
+ * Update activity_magic.py
+
+-------------------------------------------------------------------
Old:
----
metakernel-0.24.2.tar.gz
New:
----
metakernel-0.24.3.tar.gz
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Other differences:
------------------
++++++ python-metakernel.spec ++++++
--- /var/tmp/diff_new_pack.pohkqR/_old 2019-11-13 13:28:35.375714053 +0100
+++ /var/tmp/diff_new_pack.pohkqR/_new 2019-11-13 13:28:35.375714053 +0100
@@ -18,7 +18,7 @@
%{?!python_module:%define python_module() python-%{**} python3-%{**}}
Name: python-metakernel
-Version: 0.24.2
+Version: 0.24.3
Release: 0
Summary: Metakernel for Jupyter
License: BSD-3-Clause
++++++ metakernel-0.24.2.tar.gz -> metakernel-0.24.3.tar.gz ++++++
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/metakernel-0.24.2/PKG-INFO
new/metakernel-0.24.3/PKG-INFO
--- old/metakernel-0.24.2/PKG-INFO 2019-06-05 10:59:55.000000000 +0200
+++ new/metakernel-0.24.3/PKG-INFO 2019-09-14 17:11:19.000000000 +0200
@@ -1,236 +1,236 @@
-Metadata-Version: 2.1
-Name: metakernel
-Version: 0.24.2
-Summary: Metakernel for Jupyter
-Home-page: https://github.com/Calysto/metakernel
-Author: Steven Silvester
-Author-email: [email protected]
-License: UNKNOWN
-Description: A Jupyter kernel base class in Python which includes core magic
functions (including help, command and file path completion, parallel and
distributed processing, downloads, and much more).
-
- .. image:: https://badge.fury.io/py/metakernel.png/
- :target: http://badge.fury.io/py/metakernel
-
- .. image::
https://coveralls.io/repos/Calysto/metakernel/badge.png?branch=master
- :target: https://coveralls.io/r/Calysto/metakernel
-
- .. image:: https://travis-ci.org/Calysto/metakernel.svg
- :target: https://travis-ci.org/Calysto/metakernel
-
- .. image::
https://anaconda.org/conda-forge/metakernel/badges/version.svg
- :target: https://anaconda.org/conda-forge/metakernel
-
- .. image::
https://anaconda.org/conda-forge/metakernel/badges/downloads.svg
- :target: https://anaconda.org/conda-forge/metakernel
-
-
- See Jupyter's docs on `wrapper kernels
- <http://jupyter-client.readthedocs.io/en/stable/wrapperkernels.html>`_.
-
- Additional magics can be installed within the new kernel package under
a `magics` subpackage.
-
-
- Features
- -------------
- - Basic set of line and cell magics for all kernels.
- - Python magic for accessing python interpreter.
- - Run kernels in parallel.
- - Shell magics.
- - Classroom management magics.
- - Tab completion for magics and file paths.
- - Help for magics using ? or Shift+Tab.
- - Plot magic for setting default plot behavior.
-
- Kernels based on Metakernel
- ---------------------------
-
- - matlab_kernel, https://github.com/Calysto/matlab_kernel
- - octave_kernel, https://github.com/Calysto/octave_kernel
- - calysto_scheme, https://github.com/Calysto/calysto_scheme
- - calysto_processing, https://github.com/Calysto/calysto_processing
- - java9_kernel, https://github.com/Bachmann1234/java9_kernel
- - xonsh_kernel, https://github.com/Calysto/xonsh_kernel
- - calysto_hy, https://github.com/Calysto/calysto_hy
- - gnuplot_kernel, https://github.com/has2k1/gnuplot_kernel
- - spylon_kernel, https://github.com/mariusvniekerk/spylon-kernel
- - wolfram_kernel, https://github.com/mmatera/iwolfram
- - sas_kernel, https://github.com/palmer0914/sas_kernel
- - pysysh_kernel, https://github.com/Jaesin/psysh_kernel
- - calysto_bash, https://github.com/Calysto/calysto_bash
-
- ... and many others.
-
- Installation
- ----------------
- You can install Metakernel through ``pip``:
-
- .. code::bash
-
- pip install metakernel --upgrade
-
- Installing `metakernel` from the `conda-forge` channel can be achieved
by adding `conda-forge` to your channels with:
-
- .. code::bash
-
- conda config --add channels conda-forge
-
- Once the `conda-forge` channel has been enabled, `metakernel` can be
installed with:
-
- .. code::bash
-
- conda install metakernel
-
- It is possible to list all of the versions of `metakernel` available
on your platform with:
-
- .. code::bash
-
- conda search metakernel --channel conda-forge
-
-
- Use MetaKernel Magics in IPython
- --------------------------------
-
- Although MetaKernel is a system for building new kernels, you can use
a subset of the magics in the IPython kernel.
-
- .. code:: python
-
- from metakernel import register_ipython_magics
- register_ipython_magics()
-
- Put the following in your (or a system-wide) ``ipython_config.py``
file:
-
- .. code:: python
-
- # /etc/ipython/ipython_config.py
- c = get_config()
- startup = [
- 'from metakernel import register_ipython_magics',
- 'register_ipython_magics()',
- ]
- c.InteractiveShellApp.exec_lines = startup
-
- Use MetaKernel Languages in Parallel
-
- To use a MetaKernel language in parallel, do the following:
-
- 1. Make sure that the Python module `ipyparallel` is installed. In the
shell, type:
-
- .. code:: bash
-
- pip install ipyparallel
-
-
- 2. To enable the extension in the notebook, in the shell, type:
-
- .. code:: bash
-
- ipcluster nbextension enable
-
-
- 3. To start up a cluster, with 10 nodes, on a local IP address, in the
shell, type:
-
- .. code:: bash
-
- ipcluster start --n=10 --ip=192.168.1.108
-
-
- 4. Initialize the code to use the 10 nodes, inside the notebook from a
host kernel ``MODULE`` and ``CLASSNAME`` (can be any metakernel kernel):
-
- .. code:: bash
-
- %parallel MODULE CLASSNAME
-
-
- For example:
-
- .. code:: bash
-
- %parallel calysto_scheme CalystoScheme
-
-
- 5. Run code in parallel, inside the notebook, type:
-
- Execute a single line, in parallel:
-
- .. code:: bash
-
- %px (+ 1 1)
-
-
- Or execute the entire cell, in parallel:
-
- .. code:: bash
-
- %%px
- (* cluster_rank cluster_rank)
-
-
- Results come back in a Python list (Scheme vector), in
``cluster_rank`` order. (This will be a JSON representation in the future).
-
- Therefore, the above would produce the result:
-
- .. code:: bash
-
- #10(0 1 4 9 16 25 36 49 64 81)
-
- You can get the results back in any of the parallel magics (``%px``,
``%%px``, or ``%pmap``) in the host kernel by accessing the variable ``_``
(single underscore), or by using the ``--set_variable VARIABLE`` flag, like so:
-
- .. code:: bash
-
- %%px --set_variable results
- (* cluster_rank cluster_rank)
-
-
- Then, in the next cell, you can access ``results``.
-
- Notice that you can use the variable ``cluster_rank`` to partition
parts of a problem so that each node is working on something different.
-
- In the examples above, use ``-e`` to evaluate the code in the host
kernel as well. Note that ``cluster_rank`` is not defined on the host machine,
and that this assumes the host kernel is the same as the parallel machines.
-
-
- Configuration
- -------------
- ``Metakernel`` subclasses can be configured by the user. The
- configuration file name is determined by the ``app_name`` property of
the subclass.
- For example, in the ``Octave`` kernel, it is ``octave_kernel``. The
user of the kernel can add an ``octave_kernel_config.py`` file to their
- ``jupyter`` config path. The base ``MetaKernel`` class offers
``plot_settings`` as a configurable trait. Subclasses can define other traits
that they wish to make
- configurable.
-
- As an example:
-
- .. code:: bash
-
- cat ~/.jupyter/octave_kernel_config.py
- # use Qt as the default backend for plots
- c.OctaveKernel.plot_settings = dict(backend='qt')
-
-
- Documentation
- -----------------------
-
- Example notebooks can be viewed here_.
-
- Documentation is available online_. Magics have interactive help_ (and
online).
-
- For version information, see the Revision History_.
-
-
- .. _here:
http://nbviewer.ipython.org/github/Calysto/metakernel/tree/master/examples/
-
- .. _help:
https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md
-
- .. _online: http://Calysto.github.io/metakernel/
-
- .. _History:
https://github.com/Calysto/metakernel/blob/master/HISTORY.rst
-
-Platform: UNKNOWN
-Classifier: Framework :: IPython
-Classifier: License :: OSI Approved :: BSD License
-Classifier: Programming Language :: Python :: 3
-Classifier: Programming Language :: Python :: 2
-Classifier: Topic :: System :: Shells
-Requires: ipykernel
-Requires: pexpect (>= 4.2)
-Requires: ipyparallel
-Description-Content-Type: text/x-rst
-Provides-Extra: test
+Metadata-Version: 2.1
+Name: metakernel
+Version: 0.24.3
+Summary: Metakernel for Jupyter
+Home-page: https://github.com/Calysto/metakernel
+Author: Steven Silvester
+Author-email: [email protected]
+License: UNKNOWN
+Description: A Jupyter kernel base class in Python which includes core magic
functions (including help, command and file path completion, parallel and
distributed processing, downloads, and much more).
+
+ .. image:: https://badge.fury.io/py/metakernel.png/
+ :target: http://badge.fury.io/py/metakernel
+
+ .. image::
https://coveralls.io/repos/Calysto/metakernel/badge.png?branch=master
+ :target: https://coveralls.io/r/Calysto/metakernel
+
+ .. image:: https://travis-ci.org/Calysto/metakernel.svg
+ :target: https://travis-ci.org/Calysto/metakernel
+
+ .. image::
https://anaconda.org/conda-forge/metakernel/badges/version.svg
+ :target: https://anaconda.org/conda-forge/metakernel
+
+ .. image::
https://anaconda.org/conda-forge/metakernel/badges/downloads.svg
+ :target: https://anaconda.org/conda-forge/metakernel
+
+
+ See Jupyter's docs on `wrapper kernels
+ <http://jupyter-client.readthedocs.io/en/stable/wrapperkernels.html>`_.
+
+ Additional magics can be installed within the new kernel package under
a `magics` subpackage.
+
+
+ Features
+ -------------
+ - Basic set of line and cell magics for all kernels.
+ - Python magic for accessing python interpreter.
+ - Run kernels in parallel.
+ - Shell magics.
+ - Classroom management magics.
+ - Tab completion for magics and file paths.
+ - Help for magics using ? or Shift+Tab.
+ - Plot magic for setting default plot behavior.
+
+ Kernels based on Metakernel
+ ---------------------------
+
+ - matlab_kernel, https://github.com/Calysto/matlab_kernel
+ - octave_kernel, https://github.com/Calysto/octave_kernel
+ - calysto_scheme, https://github.com/Calysto/calysto_scheme
+ - calysto_processing, https://github.com/Calysto/calysto_processing
+ - java9_kernel, https://github.com/Bachmann1234/java9_kernel
+ - xonsh_kernel, https://github.com/Calysto/xonsh_kernel
+ - calysto_hy, https://github.com/Calysto/calysto_hy
+ - gnuplot_kernel, https://github.com/has2k1/gnuplot_kernel
+ - spylon_kernel, https://github.com/mariusvniekerk/spylon-kernel
+ - wolfram_kernel, https://github.com/mmatera/iwolfram
+ - sas_kernel, https://github.com/palmer0914/sas_kernel
+ - pysysh_kernel, https://github.com/Jaesin/psysh_kernel
+ - calysto_bash, https://github.com/Calysto/calysto_bash
+
+ ... and many others.
+
+ Installation
+ ----------------
+ You can install Metakernel through ``pip``:
+
+ .. code::bash
+
+ pip install metakernel --upgrade
+
+ Installing `metakernel` from the `conda-forge` channel can be achieved
by adding `conda-forge` to your channels with:
+
+ .. code::bash
+
+ conda config --add channels conda-forge
+
+ Once the `conda-forge` channel has been enabled, `metakernel` can be
installed with:
+
+ .. code::bash
+
+ conda install metakernel
+
+ It is possible to list all of the versions of `metakernel` available
on your platform with:
+
+ .. code::bash
+
+ conda search metakernel --channel conda-forge
+
+
+ Use MetaKernel Magics in IPython
+ --------------------------------
+
+ Although MetaKernel is a system for building new kernels, you can use
a subset of the magics in the IPython kernel.
+
+ .. code:: python
+
+ from metakernel import register_ipython_magics
+ register_ipython_magics()
+
+ Put the following in your (or a system-wide) ``ipython_config.py``
file:
+
+ .. code:: python
+
+ # /etc/ipython/ipython_config.py
+ c = get_config()
+ startup = [
+ 'from metakernel import register_ipython_magics',
+ 'register_ipython_magics()',
+ ]
+ c.InteractiveShellApp.exec_lines = startup
+
+ Use MetaKernel Languages in Parallel
+
+ To use a MetaKernel language in parallel, do the following:
+
+ 1. Make sure that the Python module `ipyparallel` is installed. In the
shell, type:
+
+ .. code:: bash
+
+ pip install ipyparallel
+
+
+ 2. To enable the extension in the notebook, in the shell, type:
+
+ .. code:: bash
+
+ ipcluster nbextension enable
+
+
+ 3. To start up a cluster, with 10 nodes, on a local IP address, in the
shell, type:
+
+ .. code:: bash
+
+ ipcluster start --n=10 --ip=192.168.1.108
+
+
+ 4. Initialize the code to use the 10 nodes, inside the notebook from a
host kernel ``MODULE`` and ``CLASSNAME`` (can be any metakernel kernel):
+
+ .. code:: bash
+
+ %parallel MODULE CLASSNAME
+
+
+ For example:
+
+ .. code:: bash
+
+ %parallel calysto_scheme CalystoScheme
+
+
+ 5. Run code in parallel, inside the notebook, type:
+
+ Execute a single line, in parallel:
+
+ .. code:: bash
+
+ %px (+ 1 1)
+
+
+ Or execute the entire cell, in parallel:
+
+ .. code:: bash
+
+ %%px
+ (* cluster_rank cluster_rank)
+
+
+ Results come back in a Python list (Scheme vector), in
``cluster_rank`` order. (This will be a JSON representation in the future).
+
+ Therefore, the above would produce the result:
+
+ .. code:: bash
+
+ #10(0 1 4 9 16 25 36 49 64 81)
+
+ You can get the results back in any of the parallel magics (``%px``,
``%%px``, or ``%pmap``) in the host kernel by accessing the variable ``_``
(single underscore), or by using the ``--set_variable VARIABLE`` flag, like so:
+
+ .. code:: bash
+
+ %%px --set_variable results
+ (* cluster_rank cluster_rank)
+
+
+ Then, in the next cell, you can access ``results``.
+
+ Notice that you can use the variable ``cluster_rank`` to partition
parts of a problem so that each node is working on something different.
+
+ In the examples above, use ``-e`` to evaluate the code in the host
kernel as well. Note that ``cluster_rank`` is not defined on the host machine,
and that this assumes the host kernel is the same as the parallel machines.
+
+
+ Configuration
+ -------------
+ ``Metakernel`` subclasses can be configured by the user. The
+ configuration file name is determined by the ``app_name`` property of
the subclass.
+ For example, in the ``Octave`` kernel, it is ``octave_kernel``. The
user of the kernel can add an ``octave_kernel_config.py`` file to their
+ ``jupyter`` config path. The base ``MetaKernel`` class offers
``plot_settings`` as a configurable trait. Subclasses can define other traits
that they wish to make
+ configurable.
+
+ As an example:
+
+ .. code:: bash
+
+ cat ~/.jupyter/octave_kernel_config.py
+ # use Qt as the default backend for plots
+ c.OctaveKernel.plot_settings = dict(backend='qt')
+
+
+ Documentation
+ -----------------------
+
+ Example notebooks can be viewed here_.
+
+ Documentation is available online_. Magics have interactive help_ (and
online).
+
+ For version information, see the Revision History_.
+
+
+ .. _here:
http://nbviewer.ipython.org/github/Calysto/metakernel/tree/master/examples/
+
+ .. _help:
https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md
+
+ .. _online: http://Calysto.github.io/metakernel/
+
+ .. _History:
https://github.com/Calysto/metakernel/blob/master/HISTORY.rst
+
+Platform: UNKNOWN
+Classifier: Framework :: IPython
+Classifier: License :: OSI Approved :: BSD License
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 2
+Classifier: Topic :: System :: Shells
+Requires: ipykernel
+Requires: pexpect (>= 4.2)
+Requires: ipyparallel
+Description-Content-Type: text/x-rst
+Provides-Extra: test
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/metakernel-0.24.2/metakernel/__init__.py
new/metakernel-0.24.3/metakernel/__init__.py
--- old/metakernel-0.24.2/metakernel/__init__.py 2019-06-05
10:59:49.000000000 +0200
+++ new/metakernel-0.24.3/metakernel/__init__.py 2019-09-14
17:11:16.000000000 +0200
@@ -9,6 +9,6 @@
__all__ = ['Magic', 'MetaKernel', 'option']
-__version__ = '0.24.2'
+__version__ = '0.24.3'
del magic, _metakernel, parser, process_metakernel
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/metakernel-0.24.2/metakernel/magics/activity_magic.py
new/metakernel-0.24.3/metakernel/magics/activity_magic.py
--- old/metakernel-0.24.2/metakernel/magics/activity_magic.py 2019-05-16
03:19:17.000000000 +0200
+++ new/metakernel-0.24.3/metakernel/magics/activity_magic.py 2019-09-14
17:10:17.000000000 +0200
@@ -162,11 +162,11 @@
print(barvalues)
def handle_submit(self, sender):
- import fcntl
- with open(self.results_filename, "a+") as g:
- fcntl.flock(g, fcntl.LOCK_EX)
+ import portalocker,os
+ with portalocker.Lock(self.results_filename, "a+") as g:
g.write("%s::%s::%s::%s\n" % (self.id, getpass.getuser(),
datetime.datetime.today(), sender.description))
- fcntl.flock(g, fcntl.LOCK_UN)
+ g.flush()
+ os.fsync(g.fileno())
self.output.clear_output()
with self.output:
print("Received: " + sender.description)
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/metakernel-0.24.2/metakernel.egg-info/PKG-INFO
new/metakernel-0.24.3/metakernel.egg-info/PKG-INFO
--- old/metakernel-0.24.2/metakernel.egg-info/PKG-INFO 2019-06-05
10:59:53.000000000 +0200
+++ new/metakernel-0.24.3/metakernel.egg-info/PKG-INFO 2019-09-14
17:11:19.000000000 +0200
@@ -1,236 +1,236 @@
-Metadata-Version: 2.1
-Name: metakernel
-Version: 0.24.2
-Summary: Metakernel for Jupyter
-Home-page: https://github.com/Calysto/metakernel
-Author: Steven Silvester
-Author-email: [email protected]
-License: UNKNOWN
-Description: A Jupyter kernel base class in Python which includes core magic
functions (including help, command and file path completion, parallel and
distributed processing, downloads, and much more).
-
- .. image:: https://badge.fury.io/py/metakernel.png/
- :target: http://badge.fury.io/py/metakernel
-
- .. image::
https://coveralls.io/repos/Calysto/metakernel/badge.png?branch=master
- :target: https://coveralls.io/r/Calysto/metakernel
-
- .. image:: https://travis-ci.org/Calysto/metakernel.svg
- :target: https://travis-ci.org/Calysto/metakernel
-
- .. image::
https://anaconda.org/conda-forge/metakernel/badges/version.svg
- :target: https://anaconda.org/conda-forge/metakernel
-
- .. image::
https://anaconda.org/conda-forge/metakernel/badges/downloads.svg
- :target: https://anaconda.org/conda-forge/metakernel
-
-
- See Jupyter's docs on `wrapper kernels
- <http://jupyter-client.readthedocs.io/en/stable/wrapperkernels.html>`_.
-
- Additional magics can be installed within the new kernel package under
a `magics` subpackage.
-
-
- Features
- -------------
- - Basic set of line and cell magics for all kernels.
- - Python magic for accessing python interpreter.
- - Run kernels in parallel.
- - Shell magics.
- - Classroom management magics.
- - Tab completion for magics and file paths.
- - Help for magics using ? or Shift+Tab.
- - Plot magic for setting default plot behavior.
-
- Kernels based on Metakernel
- ---------------------------
-
- - matlab_kernel, https://github.com/Calysto/matlab_kernel
- - octave_kernel, https://github.com/Calysto/octave_kernel
- - calysto_scheme, https://github.com/Calysto/calysto_scheme
- - calysto_processing, https://github.com/Calysto/calysto_processing
- - java9_kernel, https://github.com/Bachmann1234/java9_kernel
- - xonsh_kernel, https://github.com/Calysto/xonsh_kernel
- - calysto_hy, https://github.com/Calysto/calysto_hy
- - gnuplot_kernel, https://github.com/has2k1/gnuplot_kernel
- - spylon_kernel, https://github.com/mariusvniekerk/spylon-kernel
- - wolfram_kernel, https://github.com/mmatera/iwolfram
- - sas_kernel, https://github.com/palmer0914/sas_kernel
- - pysysh_kernel, https://github.com/Jaesin/psysh_kernel
- - calysto_bash, https://github.com/Calysto/calysto_bash
-
- ... and many others.
-
- Installation
- ----------------
- You can install Metakernel through ``pip``:
-
- .. code::bash
-
- pip install metakernel --upgrade
-
- Installing `metakernel` from the `conda-forge` channel can be achieved
by adding `conda-forge` to your channels with:
-
- .. code::bash
-
- conda config --add channels conda-forge
-
- Once the `conda-forge` channel has been enabled, `metakernel` can be
installed with:
-
- .. code::bash
-
- conda install metakernel
-
- It is possible to list all of the versions of `metakernel` available
on your platform with:
-
- .. code::bash
-
- conda search metakernel --channel conda-forge
-
-
- Use MetaKernel Magics in IPython
- --------------------------------
-
- Although MetaKernel is a system for building new kernels, you can use
a subset of the magics in the IPython kernel.
-
- .. code:: python
-
- from metakernel import register_ipython_magics
- register_ipython_magics()
-
- Put the following in your (or a system-wide) ``ipython_config.py``
file:
-
- .. code:: python
-
- # /etc/ipython/ipython_config.py
- c = get_config()
- startup = [
- 'from metakernel import register_ipython_magics',
- 'register_ipython_magics()',
- ]
- c.InteractiveShellApp.exec_lines = startup
-
- Use MetaKernel Languages in Parallel
-
- To use a MetaKernel language in parallel, do the following:
-
- 1. Make sure that the Python module `ipyparallel` is installed. In the
shell, type:
-
- .. code:: bash
-
- pip install ipyparallel
-
-
- 2. To enable the extension in the notebook, in the shell, type:
-
- .. code:: bash
-
- ipcluster nbextension enable
-
-
- 3. To start up a cluster, with 10 nodes, on a local IP address, in the
shell, type:
-
- .. code:: bash
-
- ipcluster start --n=10 --ip=192.168.1.108
-
-
- 4. Initialize the code to use the 10 nodes, inside the notebook from a
host kernel ``MODULE`` and ``CLASSNAME`` (can be any metakernel kernel):
-
- .. code:: bash
-
- %parallel MODULE CLASSNAME
-
-
- For example:
-
- .. code:: bash
-
- %parallel calysto_scheme CalystoScheme
-
-
- 5. Run code in parallel, inside the notebook, type:
-
- Execute a single line, in parallel:
-
- .. code:: bash
-
- %px (+ 1 1)
-
-
- Or execute the entire cell, in parallel:
-
- .. code:: bash
-
- %%px
- (* cluster_rank cluster_rank)
-
-
- Results come back in a Python list (Scheme vector), in
``cluster_rank`` order. (This will be a JSON representation in the future).
-
- Therefore, the above would produce the result:
-
- .. code:: bash
-
- #10(0 1 4 9 16 25 36 49 64 81)
-
- You can get the results back in any of the parallel magics (``%px``,
``%%px``, or ``%pmap``) in the host kernel by accessing the variable ``_``
(single underscore), or by using the ``--set_variable VARIABLE`` flag, like so:
-
- .. code:: bash
-
- %%px --set_variable results
- (* cluster_rank cluster_rank)
-
-
- Then, in the next cell, you can access ``results``.
-
- Notice that you can use the variable ``cluster_rank`` to partition
parts of a problem so that each node is working on something different.
-
- In the examples above, use ``-e`` to evaluate the code in the host
kernel as well. Note that ``cluster_rank`` is not defined on the host machine,
and that this assumes the host kernel is the same as the parallel machines.
-
-
- Configuration
- -------------
- ``Metakernel`` subclasses can be configured by the user. The
- configuration file name is determined by the ``app_name`` property of
the subclass.
- For example, in the ``Octave`` kernel, it is ``octave_kernel``. The
user of the kernel can add an ``octave_kernel_config.py`` file to their
- ``jupyter`` config path. The base ``MetaKernel`` class offers
``plot_settings`` as a configurable trait. Subclasses can define other traits
that they wish to make
- configurable.
-
- As an example:
-
- .. code:: bash
-
- cat ~/.jupyter/octave_kernel_config.py
- # use Qt as the default backend for plots
- c.OctaveKernel.plot_settings = dict(backend='qt')
-
-
- Documentation
- -----------------------
-
- Example notebooks can be viewed here_.
-
- Documentation is available online_. Magics have interactive help_ (and
online).
-
- For version information, see the Revision History_.
-
-
- .. _here:
http://nbviewer.ipython.org/github/Calysto/metakernel/tree/master/examples/
-
- .. _help:
https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md
-
- .. _online: http://Calysto.github.io/metakernel/
-
- .. _History:
https://github.com/Calysto/metakernel/blob/master/HISTORY.rst
-
-Platform: UNKNOWN
-Classifier: Framework :: IPython
-Classifier: License :: OSI Approved :: BSD License
-Classifier: Programming Language :: Python :: 3
-Classifier: Programming Language :: Python :: 2
-Classifier: Topic :: System :: Shells
-Requires: ipykernel
-Requires: pexpect (>= 4.2)
-Requires: ipyparallel
-Description-Content-Type: text/x-rst
-Provides-Extra: test
+Metadata-Version: 2.1
+Name: metakernel
+Version: 0.24.3
+Summary: Metakernel for Jupyter
+Home-page: https://github.com/Calysto/metakernel
+Author: Steven Silvester
+Author-email: [email protected]
+License: UNKNOWN
+Description: A Jupyter kernel base class in Python which includes core magic
functions (including help, command and file path completion, parallel and
distributed processing, downloads, and much more).
+
+ .. image:: https://badge.fury.io/py/metakernel.png/
+ :target: http://badge.fury.io/py/metakernel
+
+ .. image::
https://coveralls.io/repos/Calysto/metakernel/badge.png?branch=master
+ :target: https://coveralls.io/r/Calysto/metakernel
+
+ .. image:: https://travis-ci.org/Calysto/metakernel.svg
+ :target: https://travis-ci.org/Calysto/metakernel
+
+ .. image::
https://anaconda.org/conda-forge/metakernel/badges/version.svg
+ :target: https://anaconda.org/conda-forge/metakernel
+
+ .. image::
https://anaconda.org/conda-forge/metakernel/badges/downloads.svg
+ :target: https://anaconda.org/conda-forge/metakernel
+
+
+ See Jupyter's docs on `wrapper kernels
+ <http://jupyter-client.readthedocs.io/en/stable/wrapperkernels.html>`_.
+
+ Additional magics can be installed within the new kernel package under
a `magics` subpackage.
+
+
+ Features
+ -------------
+ - Basic set of line and cell magics for all kernels.
+ - Python magic for accessing python interpreter.
+ - Run kernels in parallel.
+ - Shell magics.
+ - Classroom management magics.
+ - Tab completion for magics and file paths.
+ - Help for magics using ? or Shift+Tab.
+ - Plot magic for setting default plot behavior.
+
+ Kernels based on Metakernel
+ ---------------------------
+
+ - matlab_kernel, https://github.com/Calysto/matlab_kernel
+ - octave_kernel, https://github.com/Calysto/octave_kernel
+ - calysto_scheme, https://github.com/Calysto/calysto_scheme
+ - calysto_processing, https://github.com/Calysto/calysto_processing
+ - java9_kernel, https://github.com/Bachmann1234/java9_kernel
+ - xonsh_kernel, https://github.com/Calysto/xonsh_kernel
+ - calysto_hy, https://github.com/Calysto/calysto_hy
+ - gnuplot_kernel, https://github.com/has2k1/gnuplot_kernel
+ - spylon_kernel, https://github.com/mariusvniekerk/spylon-kernel
+ - wolfram_kernel, https://github.com/mmatera/iwolfram
+ - sas_kernel, https://github.com/palmer0914/sas_kernel
+ - pysysh_kernel, https://github.com/Jaesin/psysh_kernel
+ - calysto_bash, https://github.com/Calysto/calysto_bash
+
+ ... and many others.
+
+ Installation
+ ----------------
+ You can install Metakernel through ``pip``:
+
+ .. code::bash
+
+ pip install metakernel --upgrade
+
+ Installing `metakernel` from the `conda-forge` channel can be achieved
by adding `conda-forge` to your channels with:
+
+ .. code::bash
+
+ conda config --add channels conda-forge
+
+ Once the `conda-forge` channel has been enabled, `metakernel` can be
installed with:
+
+ .. code::bash
+
+ conda install metakernel
+
+ It is possible to list all of the versions of `metakernel` available
on your platform with:
+
+ .. code::bash
+
+ conda search metakernel --channel conda-forge
+
+
+ Use MetaKernel Magics in IPython
+ --------------------------------
+
+ Although MetaKernel is a system for building new kernels, you can use
a subset of the magics in the IPython kernel.
+
+ .. code:: python
+
+ from metakernel import register_ipython_magics
+ register_ipython_magics()
+
+ Put the following in your (or a system-wide) ``ipython_config.py``
file:
+
+ .. code:: python
+
+ # /etc/ipython/ipython_config.py
+ c = get_config()
+ startup = [
+ 'from metakernel import register_ipython_magics',
+ 'register_ipython_magics()',
+ ]
+ c.InteractiveShellApp.exec_lines = startup
+
+ Use MetaKernel Languages in Parallel
+
+ To use a MetaKernel language in parallel, do the following:
+
+ 1. Make sure that the Python module `ipyparallel` is installed. In the
shell, type:
+
+ .. code:: bash
+
+ pip install ipyparallel
+
+
+ 2. To enable the extension in the notebook, in the shell, type:
+
+ .. code:: bash
+
+ ipcluster nbextension enable
+
+
+ 3. To start up a cluster, with 10 nodes, on a local IP address, in the
shell, type:
+
+ .. code:: bash
+
+ ipcluster start --n=10 --ip=192.168.1.108
+
+
+ 4. Initialize the code to use the 10 nodes, inside the notebook from a
host kernel ``MODULE`` and ``CLASSNAME`` (can be any metakernel kernel):
+
+ .. code:: bash
+
+ %parallel MODULE CLASSNAME
+
+
+ For example:
+
+ .. code:: bash
+
+ %parallel calysto_scheme CalystoScheme
+
+
+ 5. Run code in parallel, inside the notebook, type:
+
+ Execute a single line, in parallel:
+
+ .. code:: bash
+
+ %px (+ 1 1)
+
+
+ Or execute the entire cell, in parallel:
+
+ .. code:: bash
+
+ %%px
+ (* cluster_rank cluster_rank)
+
+
+ Results come back in a Python list (Scheme vector), in
``cluster_rank`` order. (This will be a JSON representation in the future).
+
+ Therefore, the above would produce the result:
+
+ .. code:: bash
+
+ #10(0 1 4 9 16 25 36 49 64 81)
+
+ You can get the results back in any of the parallel magics (``%px``,
``%%px``, or ``%pmap``) in the host kernel by accessing the variable ``_``
(single underscore), or by using the ``--set_variable VARIABLE`` flag, like so:
+
+ .. code:: bash
+
+ %%px --set_variable results
+ (* cluster_rank cluster_rank)
+
+
+ Then, in the next cell, you can access ``results``.
+
+ Notice that you can use the variable ``cluster_rank`` to partition
parts of a problem so that each node is working on something different.
+
+ In the examples above, use ``-e`` to evaluate the code in the host
kernel as well. Note that ``cluster_rank`` is not defined on the host machine,
and that this assumes the host kernel is the same as the parallel machines.
+
+
+ Configuration
+ -------------
+ ``Metakernel`` subclasses can be configured by the user. The
+ configuration file name is determined by the ``app_name`` property of
the subclass.
+ For example, in the ``Octave`` kernel, it is ``octave_kernel``. The
user of the kernel can add an ``octave_kernel_config.py`` file to their
+ ``jupyter`` config path. The base ``MetaKernel`` class offers
``plot_settings`` as a configurable trait. Subclasses can define other traits
that they wish to make
+ configurable.
+
+ As an example:
+
+ .. code:: bash
+
+ cat ~/.jupyter/octave_kernel_config.py
+ # use Qt as the default backend for plots
+ c.OctaveKernel.plot_settings = dict(backend='qt')
+
+
+ Documentation
+ -----------------------
+
+ Example notebooks can be viewed here_.
+
+ Documentation is available online_. Magics have interactive help_ (and
online).
+
+ For version information, see the Revision History_.
+
+
+ .. _here:
http://nbviewer.ipython.org/github/Calysto/metakernel/tree/master/examples/
+
+ .. _help:
https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md
+
+ .. _online: http://Calysto.github.io/metakernel/
+
+ .. _History:
https://github.com/Calysto/metakernel/blob/master/HISTORY.rst
+
+Platform: UNKNOWN
+Classifier: Framework :: IPython
+Classifier: License :: OSI Approved :: BSD License
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 2
+Classifier: Topic :: System :: Shells
+Requires: ipykernel
+Requires: pexpect (>= 4.2)
+Requires: ipyparallel
+Description-Content-Type: text/x-rst
+Provides-Extra: test
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/metakernel-0.24.2/metakernel.egg-info/SOURCES.txt
new/metakernel-0.24.3/metakernel.egg-info/SOURCES.txt
--- old/metakernel-0.24.2/metakernel.egg-info/SOURCES.txt 2019-06-05
10:59:54.000000000 +0200
+++ new/metakernel-0.24.3/metakernel.egg-info/SOURCES.txt 2019-09-14
17:11:19.000000000 +0200
@@ -108,7 +108,6 @@
metakernel_echo/README.md
metakernel_echo/metakernel_echo.py
metakernel_echo/setup.py
-metakernel_echo/__pycache__/metakernel_echo.cpython-37.pyc
metakernel_python/README.md
metakernel_python/metakernel_python.py
metakernel_python/setup.py
\ No newline at end of file
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/metakernel-0.24.2/metakernel.egg-info/requires.txt
new/metakernel-0.24.3/metakernel.egg-info/requires.txt
--- old/metakernel-0.24.2/metakernel.egg-info/requires.txt 2019-06-05
10:59:53.000000000 +0200
+++ new/metakernel-0.24.3/metakernel.egg-info/requires.txt 2019-09-14
17:11:19.000000000 +0200
@@ -1,6 +1,7 @@
ipykernel
pexpect>=4.2
ipyparallel
+portalocker
[test]
pytest
Binary files
old/metakernel-0.24.2/metakernel_echo/__pycache__/metakernel_echo.cpython-37.pyc
and
new/metakernel-0.24.3/metakernel_echo/__pycache__/metakernel_echo.cpython-37.pyc
differ
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/metakernel-0.24.2/setup.cfg
new/metakernel-0.24.3/setup.cfg
--- old/metakernel-0.24.2/setup.cfg 2019-06-05 10:59:55.000000000 +0200
+++ new/metakernel-0.24.3/setup.cfg 2019-09-14 17:11:19.000000000 +0200
@@ -1,22 +1,22 @@
-[build_sphinx]
-source-dir = docs
-build-dir = docs/build
-all_files = 1
-
-[upload_sphinx]
-upload-dir = docs/build/html
-
-[wheel]
-universal = 1
-
-[metadata]
-license_file = LICENSE.txt
-
-[tool:pytest]
-addopts = --doctest-modules
-norecursedirs = images metakernel_python
-
-[egg_info]
-tag_build =
-tag_date = 0
-
+[build_sphinx]
+source-dir = docs
+build-dir = docs/build
+all_files = 1
+
+[upload_sphinx]
+upload-dir = docs/build/html
+
+[wheel]
+universal = 1
+
+[metadata]
+license_file = LICENSE.txt
+
+[tool:pytest]
+addopts = --doctest-modules
+norecursedirs = images metakernel_python
+
+[egg_info]
+tag_build =
+tag_date = 0
+
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/metakernel-0.24.2/setup.py
new/metakernel-0.24.3/setup.py
--- old/metakernel-0.24.2/setup.py 2019-06-04 00:00:39.000000000 +0200
+++ new/metakernel-0.24.3/setup.py 2019-09-14 17:10:17.000000000 +0200
@@ -27,7 +27,7 @@
author_email='[email protected]',
url='https://github.com/Calysto/metakernel',
requires=[ipykernel_requires, 'pexpect (>= 4.2)', 'ipyparallel'],
- install_requires=[ipykernel_install_requires, 'pexpect>=4.2',
'ipyparallel'],
+ install_requires=[ipykernel_install_requires, 'pexpect>=4.2',
'ipyparallel','portalocker'],
extras_require={
'test': ['pytest', 'pytest-cov', 'requests']
},
