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@@ -0,0 +1 @@ +/dask_labextension-6.1.0.tar.gz diff --git a/python-dask-labextension.spec b/python-dask-labextension.spec new file mode 100644 index 0000000..c074cb2 --- /dev/null +++ b/python-dask-labextension.spec @@ -0,0 +1,778 @@ +%global _empty_manifest_terminate_build 0 +Name: python-dask-labextension +Version: 6.1.0 +Release: 1 +Summary: A JupyterLab extension for Dask. +License: BSD-3-Clause +URL: https://github.com/dask/dask-labextension +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/2c/a6/f707660c2bebb2394dd0f879b193bb235c039f722ab793dd885e97e2d09d/dask_labextension-6.1.0.tar.gz +BuildArch: noarch + +Requires: python3-bokeh +Requires: python3-distributed +Requires: python3-jupyter-server-proxy +Requires: python3-jupyterlab + +%description +# Dask JupyterLab Extension + +[](https://travis-ci.org/dask/dask-labextension) [](https://www.npmjs.com/package/dask-labextension) [](https://www.npmjs.com/package/dask-labextension) [](https://libraries.io/npm/dask-labextension) + +This package provides a JupyterLab extension to manage Dask clusters, +as well as embed Dask's dashboard plots directly into JupyterLab panes. + + + +## Explanatory Video (5 minutes) + +<a href="http://www.youtube.com/watch?feature=player_embedded&v=EX_voquHdk0 " + target="_blank"> +<img src="http://img.youtube.com/vi/EX_voquHdk0/0.jpg" + alt="Dask + JupyterLab Screencast" width="560" height="315" border="10" /> +</a> + +## Requirements + +JupyterLab >= 1.0 +distributed >= 1.24.1 + +## Installation + +To install the Dask JupyterLab extension you will need to have JupyterLab installed. +For JupyterLab < 3.0, you will also need [Node.js](https://nodejs.org/) version >= 12. +These are available through a variety of sources. +One source common to Python users is the conda package manager. + +```bash +conda install jupyterlab +conda install -c conda-forge nodejs +``` + +### JupyterLab 3.0 or greater + +You should be able to install this extension with pip or conda, +and start using it immediately, e.g. + +```bash +pip install dask-labextension +``` + +### JupyterLab 3.x + +This extension includes both client-side and server-side components. +Prior to JupyterLab 3.0 these needed to be installed separately, +with node available on the machine. + +The server-side component can be installed via pip or conda-forge: + +```bash +pip install dask_labextension +``` + +```bash +conda install -c conda-forge dask-labextension +``` + +You then build the client-side extension into JupyterLab with: + +```bash +jupyter labextension install dask-labextension +``` + +If you are running Notebook 5.2 or earlier, enable the server extension by running + +```bash +jupyter serverextension enable --py --sys-prefix dask_labextension +``` + +## Configuration of Dask cluster management + +This extension has the ability to launch and manage several kinds of Dask clusters, +including local clusters and kubernetes clusters. +Options for how to launch these clusters are set via the +[dask configuration system](http://docs.dask.org/en/latest/configuration.html#configuration), +typically a `.yml` file on disk. + +By default the extension launches a `LocalCluster`, for which the configuration is: + +```yaml +labextension: + factory: + module: 'dask.distributed' + class: 'LocalCluster' + args: [] + kwargs: {} + default: + workers: null + adapt: + null + # minimum: 0 + # maximum: 10 + initial: + [] + # - name: "My Big Cluster" + # workers: 100 + # - name: "Adaptive Cluster" + # adapt: + # minimum: 0 + # maximum: 50 +``` + +In this configuration, `factory` gives the module, class name, and arguments needed to create the cluster. +The `default` key describes the initial number of workers for the cluster, as well as whether it is adaptive. +The `initial` key gives a list of initial clusters to start upon launch of the notebook server. + +In addition to `LocalCluster`, this extension has been used to launch several other Dask cluster +objects, a few examples of which are: + +- A SLURM cluster, using + +```yaml +labextension: + factory: + module: 'dask_jobqueue' + class: 'SLURMCluster' + args: [] + kwargs: {} +``` + +- A PBS cluster, using + +```yaml +labextension: + factory: + module: 'dask_jobqueue' + class: 'PBSCluster' + args: [] + kwargs: {} +``` + +- A [Kubernetes cluster](https://github.com/pangeo-data/pangeo-cloud-federation/blob/8f7f4bf9963ef1ed180dd20c952ff1aa8df54ca2/deployments/ocean/image/binder/dask_config.yaml#L37-L42), using + +```yaml +labextension: + factory: + module: dask_kubernetes + class: KubeCluster + args: [] + kwargs: {} +``` + +## Configuring a default layout + +This extension can store a default layout for the Dask dashboard panes, +which is useful if you find yourself reaching for the same dashboard charts over and over. +You can launch the default layout via the command palette, +or by going to the File menu and choosing "Launch Dask Dashboard Layout". + +Default layouts can be configured via the JupyterLab config system +(either using the JSON editor or the user interface). +Specify a layout by writing a JSON object keyed by the +[individual charts](https://github.com/dask/distributed/blob/f31fbde748294065ed70dd5c4399821fa664a9f1/distributed/dashboard/scheduler.py#L72-L117) +you would like to open. +Each chart is opened with a `mode`, and a `ref`. +`mode` refers to how the chart is to be added to the workspace. +For example, if you want to split a panel and add the new one to the right, choose `split-right`. +Other options are `split-top`, `split-bottom`, `split-left`, `tab-after`, and `tab-before`. +`ref` refers to the panel to which `mode` is applied, and might be the names of other dashboard panels. +If `ref` is `null`, the panel in question is added at the top of the layout hierarchy. + +A concrete example of a default layout is + +```json +{ + "individual-task-stream": { + "mode": "split-right", + "ref": null + }, + "individual-workers-memory": { + "mode": "split-bottom", + "ref": "individual-task-stream" + }, + "individual-progress": { + "mode": "split-right", + "ref": "individual-workers-memory" + } +} +``` + +which adds the task stream to the right of the workspace, +then adds the worker memory chart below the task stream, +then adds the progress chart to the right of the worker memory chart. + +## Development install + +As described in the [JupyterLab documentation](https://jupyterlab.readthedocs.io/en/stable/extension/extension_dev.html#developing-a-prebuilt-extension) +for a development install of the labextension you can run the following in this directory: + +```bash +jlpm # Install npm package dependencies +jlpm build # Compile the TypeScript sources to Javascript +jupyter labextension develop . --overwrite # Install the current directory as an extension +``` + +To rebuild the extension: + +```bash +jlpm build +``` + +You should then be able to refresh the JupyterLab page +and it will pick up the changes to the extension. + +To run an editable install of the server extension, run + +```bash +pip install -e . +jupyter serverextension enable --sys-prefix dask_labextension +``` + +## Publishing + +This application is distributed as two subpackages. + +The JupyterLab frontend part is published to [npm](https://www.npmjs.com/package/dask-labextension), +and the server-side part to [PyPI](https://pypi.org/project/dask-labextension/). + +Releases for both packages are done with the `jlpm` tool, `git` and Travis CI. + +_Note: Package versions are not prefixed with the letter `v`. You will need to disable this._ + +```console +$ jlpm config set version-tag-prefix "" +``` + +Making a release + +```console +$ jlpm version [--major|--minor|--patch] # updates package.json and creates git commit and tag +$ git push upstream main && git push upstream main --tags # pushes tags to GitHub which triggers Travis CI to build and deploy +``` + + +%package -n python3-dask-labextension +Summary: A JupyterLab extension for Dask. +Provides: python-dask-labextension +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-dask-labextension +# Dask JupyterLab Extension + +[](https://travis-ci.org/dask/dask-labextension) [](https://www.npmjs.com/package/dask-labextension) [](https://www.npmjs.com/package/dask-labextension) [](https://libraries.io/npm/dask-labextension) + +This package provides a JupyterLab extension to manage Dask clusters, +as well as embed Dask's dashboard plots directly into JupyterLab panes. + + + +## Explanatory Video (5 minutes) + +<a href="http://www.youtube.com/watch?feature=player_embedded&v=EX_voquHdk0 " + target="_blank"> +<img src="http://img.youtube.com/vi/EX_voquHdk0/0.jpg" + alt="Dask + JupyterLab Screencast" width="560" height="315" border="10" /> +</a> + +## Requirements + +JupyterLab >= 1.0 +distributed >= 1.24.1 + +## Installation + +To install the Dask JupyterLab extension you will need to have JupyterLab installed. +For JupyterLab < 3.0, you will also need [Node.js](https://nodejs.org/) version >= 12. +These are available through a variety of sources. +One source common to Python users is the conda package manager. + +```bash +conda install jupyterlab +conda install -c conda-forge nodejs +``` + +### JupyterLab 3.0 or greater + +You should be able to install this extension with pip or conda, +and start using it immediately, e.g. + +```bash +pip install dask-labextension +``` + +### JupyterLab 3.x + +This extension includes both client-side and server-side components. +Prior to JupyterLab 3.0 these needed to be installed separately, +with node available on the machine. + +The server-side component can be installed via pip or conda-forge: + +```bash +pip install dask_labextension +``` + +```bash +conda install -c conda-forge dask-labextension +``` + +You then build the client-side extension into JupyterLab with: + +```bash +jupyter labextension install dask-labextension +``` + +If you are running Notebook 5.2 or earlier, enable the server extension by running + +```bash +jupyter serverextension enable --py --sys-prefix dask_labextension +``` + +## Configuration of Dask cluster management + +This extension has the ability to launch and manage several kinds of Dask clusters, +including local clusters and kubernetes clusters. +Options for how to launch these clusters are set via the +[dask configuration system](http://docs.dask.org/en/latest/configuration.html#configuration), +typically a `.yml` file on disk. + +By default the extension launches a `LocalCluster`, for which the configuration is: + +```yaml +labextension: + factory: + module: 'dask.distributed' + class: 'LocalCluster' + args: [] + kwargs: {} + default: + workers: null + adapt: + null + # minimum: 0 + # maximum: 10 + initial: + [] + # - name: "My Big Cluster" + # workers: 100 + # - name: "Adaptive Cluster" + # adapt: + # minimum: 0 + # maximum: 50 +``` + +In this configuration, `factory` gives the module, class name, and arguments needed to create the cluster. +The `default` key describes the initial number of workers for the cluster, as well as whether it is adaptive. +The `initial` key gives a list of initial clusters to start upon launch of the notebook server. + +In addition to `LocalCluster`, this extension has been used to launch several other Dask cluster +objects, a few examples of which are: + +- A SLURM cluster, using + +```yaml +labextension: + factory: + module: 'dask_jobqueue' + class: 'SLURMCluster' + args: [] + kwargs: {} +``` + +- A PBS cluster, using + +```yaml +labextension: + factory: + module: 'dask_jobqueue' + class: 'PBSCluster' + args: [] + kwargs: {} +``` + +- A [Kubernetes cluster](https://github.com/pangeo-data/pangeo-cloud-federation/blob/8f7f4bf9963ef1ed180dd20c952ff1aa8df54ca2/deployments/ocean/image/binder/dask_config.yaml#L37-L42), using + +```yaml +labextension: + factory: + module: dask_kubernetes + class: KubeCluster + args: [] + kwargs: {} +``` + +## Configuring a default layout + +This extension can store a default layout for the Dask dashboard panes, +which is useful if you find yourself reaching for the same dashboard charts over and over. +You can launch the default layout via the command palette, +or by going to the File menu and choosing "Launch Dask Dashboard Layout". + +Default layouts can be configured via the JupyterLab config system +(either using the JSON editor or the user interface). +Specify a layout by writing a JSON object keyed by the +[individual charts](https://github.com/dask/distributed/blob/f31fbde748294065ed70dd5c4399821fa664a9f1/distributed/dashboard/scheduler.py#L72-L117) +you would like to open. +Each chart is opened with a `mode`, and a `ref`. +`mode` refers to how the chart is to be added to the workspace. +For example, if you want to split a panel and add the new one to the right, choose `split-right`. +Other options are `split-top`, `split-bottom`, `split-left`, `tab-after`, and `tab-before`. +`ref` refers to the panel to which `mode` is applied, and might be the names of other dashboard panels. +If `ref` is `null`, the panel in question is added at the top of the layout hierarchy. + +A concrete example of a default layout is + +```json +{ + "individual-task-stream": { + "mode": "split-right", + "ref": null + }, + "individual-workers-memory": { + "mode": "split-bottom", + "ref": "individual-task-stream" + }, + "individual-progress": { + "mode": "split-right", + "ref": "individual-workers-memory" + } +} +``` + +which adds the task stream to the right of the workspace, +then adds the worker memory chart below the task stream, +then adds the progress chart to the right of the worker memory chart. + +## Development install + +As described in the [JupyterLab documentation](https://jupyterlab.readthedocs.io/en/stable/extension/extension_dev.html#developing-a-prebuilt-extension) +for a development install of the labextension you can run the following in this directory: + +```bash +jlpm # Install npm package dependencies +jlpm build # Compile the TypeScript sources to Javascript +jupyter labextension develop . --overwrite # Install the current directory as an extension +``` + +To rebuild the extension: + +```bash +jlpm build +``` + +You should then be able to refresh the JupyterLab page +and it will pick up the changes to the extension. + +To run an editable install of the server extension, run + +```bash +pip install -e . +jupyter serverextension enable --sys-prefix dask_labextension +``` + +## Publishing + +This application is distributed as two subpackages. + +The JupyterLab frontend part is published to [npm](https://www.npmjs.com/package/dask-labextension), +and the server-side part to [PyPI](https://pypi.org/project/dask-labextension/). + +Releases for both packages are done with the `jlpm` tool, `git` and Travis CI. + +_Note: Package versions are not prefixed with the letter `v`. You will need to disable this._ + +```console +$ jlpm config set version-tag-prefix "" +``` + +Making a release + +```console +$ jlpm version [--major|--minor|--patch] # updates package.json and creates git commit and tag +$ git push upstream main && git push upstream main --tags # pushes tags to GitHub which triggers Travis CI to build and deploy +``` + + +%package help +Summary: Development documents and examples for dask-labextension +Provides: python3-dask-labextension-doc +%description help +# Dask JupyterLab Extension + +[](https://travis-ci.org/dask/dask-labextension) [](https://www.npmjs.com/package/dask-labextension) [](https://www.npmjs.com/package/dask-labextension) [](https://libraries.io/npm/dask-labextension) + +This package provides a JupyterLab extension to manage Dask clusters, +as well as embed Dask's dashboard plots directly into JupyterLab panes. + + + +## Explanatory Video (5 minutes) + +<a href="http://www.youtube.com/watch?feature=player_embedded&v=EX_voquHdk0 " + target="_blank"> +<img src="http://img.youtube.com/vi/EX_voquHdk0/0.jpg" + alt="Dask + JupyterLab Screencast" width="560" height="315" border="10" /> +</a> + +## Requirements + +JupyterLab >= 1.0 +distributed >= 1.24.1 + +## Installation + +To install the Dask JupyterLab extension you will need to have JupyterLab installed. +For JupyterLab < 3.0, you will also need [Node.js](https://nodejs.org/) version >= 12. +These are available through a variety of sources. +One source common to Python users is the conda package manager. + +```bash +conda install jupyterlab +conda install -c conda-forge nodejs +``` + +### JupyterLab 3.0 or greater + +You should be able to install this extension with pip or conda, +and start using it immediately, e.g. + +```bash +pip install dask-labextension +``` + +### JupyterLab 3.x + +This extension includes both client-side and server-side components. +Prior to JupyterLab 3.0 these needed to be installed separately, +with node available on the machine. + +The server-side component can be installed via pip or conda-forge: + +```bash +pip install dask_labextension +``` + +```bash +conda install -c conda-forge dask-labextension +``` + +You then build the client-side extension into JupyterLab with: + +```bash +jupyter labextension install dask-labextension +``` + +If you are running Notebook 5.2 or earlier, enable the server extension by running + +```bash +jupyter serverextension enable --py --sys-prefix dask_labextension +``` + +## Configuration of Dask cluster management + +This extension has the ability to launch and manage several kinds of Dask clusters, +including local clusters and kubernetes clusters. +Options for how to launch these clusters are set via the +[dask configuration system](http://docs.dask.org/en/latest/configuration.html#configuration), +typically a `.yml` file on disk. + +By default the extension launches a `LocalCluster`, for which the configuration is: + +```yaml +labextension: + factory: + module: 'dask.distributed' + class: 'LocalCluster' + args: [] + kwargs: {} + default: + workers: null + adapt: + null + # minimum: 0 + # maximum: 10 + initial: + [] + # - name: "My Big Cluster" + # workers: 100 + # - name: "Adaptive Cluster" + # adapt: + # minimum: 0 + # maximum: 50 +``` + +In this configuration, `factory` gives the module, class name, and arguments needed to create the cluster. +The `default` key describes the initial number of workers for the cluster, as well as whether it is adaptive. +The `initial` key gives a list of initial clusters to start upon launch of the notebook server. + +In addition to `LocalCluster`, this extension has been used to launch several other Dask cluster +objects, a few examples of which are: + +- A SLURM cluster, using + +```yaml +labextension: + factory: + module: 'dask_jobqueue' + class: 'SLURMCluster' + args: [] + kwargs: {} +``` + +- A PBS cluster, using + +```yaml +labextension: + factory: + module: 'dask_jobqueue' + class: 'PBSCluster' + args: [] + kwargs: {} +``` + +- A [Kubernetes cluster](https://github.com/pangeo-data/pangeo-cloud-federation/blob/8f7f4bf9963ef1ed180dd20c952ff1aa8df54ca2/deployments/ocean/image/binder/dask_config.yaml#L37-L42), using + +```yaml +labextension: + factory: + module: dask_kubernetes + class: KubeCluster + args: [] + kwargs: {} +``` + +## Configuring a default layout + +This extension can store a default layout for the Dask dashboard panes, +which is useful if you find yourself reaching for the same dashboard charts over and over. +You can launch the default layout via the command palette, +or by going to the File menu and choosing "Launch Dask Dashboard Layout". + +Default layouts can be configured via the JupyterLab config system +(either using the JSON editor or the user interface). +Specify a layout by writing a JSON object keyed by the +[individual charts](https://github.com/dask/distributed/blob/f31fbde748294065ed70dd5c4399821fa664a9f1/distributed/dashboard/scheduler.py#L72-L117) +you would like to open. +Each chart is opened with a `mode`, and a `ref`. +`mode` refers to how the chart is to be added to the workspace. +For example, if you want to split a panel and add the new one to the right, choose `split-right`. +Other options are `split-top`, `split-bottom`, `split-left`, `tab-after`, and `tab-before`. +`ref` refers to the panel to which `mode` is applied, and might be the names of other dashboard panels. +If `ref` is `null`, the panel in question is added at the top of the layout hierarchy. + +A concrete example of a default layout is + +```json +{ + "individual-task-stream": { + "mode": "split-right", + "ref": null + }, + "individual-workers-memory": { + "mode": "split-bottom", + "ref": "individual-task-stream" + }, + "individual-progress": { + "mode": "split-right", + "ref": "individual-workers-memory" + } +} +``` + +which adds the task stream to the right of the workspace, +then adds the worker memory chart below the task stream, +then adds the progress chart to the right of the worker memory chart. + +## Development install + +As described in the [JupyterLab documentation](https://jupyterlab.readthedocs.io/en/stable/extension/extension_dev.html#developing-a-prebuilt-extension) +for a development install of the labextension you can run the following in this directory: + +```bash +jlpm # Install npm package dependencies +jlpm build # Compile the TypeScript sources to Javascript +jupyter labextension develop . --overwrite # Install the current directory as an extension +``` + +To rebuild the extension: + +```bash +jlpm build +``` + +You should then be able to refresh the JupyterLab page +and it will pick up the changes to the extension. + +To run an editable install of the server extension, run + +```bash +pip install -e . +jupyter serverextension enable --sys-prefix dask_labextension +``` + +## Publishing + +This application is distributed as two subpackages. + +The JupyterLab frontend part is published to [npm](https://www.npmjs.com/package/dask-labextension), +and the server-side part to [PyPI](https://pypi.org/project/dask-labextension/). + +Releases for both packages are done with the `jlpm` tool, `git` and Travis CI. + +_Note: Package versions are not prefixed with the letter `v`. You will need to disable this._ + +```console +$ jlpm config set version-tag-prefix "" +``` + +Making a release + +```console +$ jlpm version [--major|--minor|--patch] # updates package.json and creates git commit and tag +$ git push upstream main && git push upstream main --tags # pushes tags to GitHub which triggers Travis CI to build and deploy +``` + + +%prep +%autosetup -n dask-labextension-6.1.0 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-dask-labextension -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 6.1.0-1 +- Package Spec generated @@ -0,0 +1 @@ +031dc28659d322bf77f381d45447df47 dask_labextension-6.1.0.tar.gz |