%global _empty_manifest_terminate_build 0 Name: python-lckr-jupyterlab-variableinspector Version: 3.0.9 Release: 1 Summary: Variable inspector extension for JupyterLab License: BSD-3-Clause URL: https://github.com/lckr/jupyterlab-variableInspector.git Source0: https://mirrors.nju.edu.cn/pypi/web/packages/81/52/db62d097de82c65cf25847b9bbe2fdddda0e40968f0c9752ea360b8b5060/lckr_jupyterlab_variableinspector-3.0.9.tar.gz BuildArch: noarch %description # jupyterlab_variableinspector ![PyPi_Version](https://img.shields.io/pypi/v/lckr-jupyterlab-variableinspector) ![Build](https://github.com/lckr/jupyterlab-variableInspector/workflows/Build/badge.svg) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/lckr/jupyterlab-variableInspector.git/master?urlpath=lab) [![GPLv3 License](https://img.shields.io/badge/License-GPL%20v3-yellow.svg)](https://opensource.org/licenses/) Jupyterlab extension that shows currently used variables and their values. Contributions in any form are welcome! ## Features ![Demogif](early_demo.gif) - Allows inspection of variables for both consoles and notebooks. - Allows inspection of matrices in a datagrid-viewer. This might not work for large matrices. - Allows an inline and interactive inspection of Jupyter Widgets. ### Supported Languages - This extension is currently targets `python` as a main language but also supports the following languages with different levels of feature completeness - `R` - `scala` via the [almond kernel](https://github.com/almond-sh/almond) ### How it Works In order to allow variabale inspection, all content that is displayed first need to be sent from the kernel to the front end. Therefore, opening large data frames with the datagrid viewer can dramatically increase your occupied memory and *significantly slow down* your browser. Use at your own risk. ## Requirements * JupyterLab >= 3.0 ### Requirements for `python` functionality - `pandas` and `numpy` are required to enable matrix inspection. - `pyspark` for spark support. - `tensorflow` and `keras` to allow inspection of tf objects. - `torch` for PyTorch support. ### Requirements for `R` functionality - The `repr` library. ### Requirements for `ipywidgets` functionality The variable inspector can also display Jupyter interactive widgets: ![ipywidgets](./ipywidgets.png) The requirements for this functionality are: - `ipywidgets` - Support for widgets in JupyterLab: `jupyter labextension install @jupyter-widgets/jupyterlab-manager` ## Install **NOTE:** The main way to install this extension is via pip as described below. ```bash pip install lckr-jupyterlab-variableinspector ``` Alternatively, one can install the extension from npmjs via: ```bash jupyter labextension install @lckr/jupyterlab_variableinspector ``` or via the extension manager that comes built-in with Jupyterlab ## Contributing ### Development install Note: You will need NodeJS to build the extension package. The `jlpm` command is JupyterLab's pinned version of [yarn](https://yarnpkg.com/) that is installed with JupyterLab. You may use `yarn` or `npm` in lieu of `jlpm` below. ```bash # Clone the repo to your local environment # Change directory to the lckr_jupyterlab_variableinspector directory # Install package in development mode pip install -e . # Link your development version of the extension with JupyterLab jupyter labextension develop . --overwrite # Rebuild extension Typescript source after making changes jlpm run build ``` You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension. ```bash # Watch the source directory in one terminal, automatically rebuilding when needed jlpm run watch # Run JupyterLab in another terminal jupyter lab ``` With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt). By default, the `jlpm run build` command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command: ```bash jupyter lab build --minimize=False ``` ### Uninstall ```bash pip uninstall lckr_jupyterlab_variableinspector ``` %package -n python3-lckr-jupyterlab-variableinspector Summary: Variable inspector extension for JupyterLab Provides: python-lckr-jupyterlab-variableinspector BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-lckr-jupyterlab-variableinspector # jupyterlab_variableinspector ![PyPi_Version](https://img.shields.io/pypi/v/lckr-jupyterlab-variableinspector) ![Build](https://github.com/lckr/jupyterlab-variableInspector/workflows/Build/badge.svg) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/lckr/jupyterlab-variableInspector.git/master?urlpath=lab) [![GPLv3 License](https://img.shields.io/badge/License-GPL%20v3-yellow.svg)](https://opensource.org/licenses/) Jupyterlab extension that shows currently used variables and their values. Contributions in any form are welcome! ## Features ![Demogif](early_demo.gif) - Allows inspection of variables for both consoles and notebooks. - Allows inspection of matrices in a datagrid-viewer. This might not work for large matrices. - Allows an inline and interactive inspection of Jupyter Widgets. ### Supported Languages - This extension is currently targets `python` as a main language but also supports the following languages with different levels of feature completeness - `R` - `scala` via the [almond kernel](https://github.com/almond-sh/almond) ### How it Works In order to allow variabale inspection, all content that is displayed first need to be sent from the kernel to the front end. Therefore, opening large data frames with the datagrid viewer can dramatically increase your occupied memory and *significantly slow down* your browser. Use at your own risk. ## Requirements * JupyterLab >= 3.0 ### Requirements for `python` functionality - `pandas` and `numpy` are required to enable matrix inspection. - `pyspark` for spark support. - `tensorflow` and `keras` to allow inspection of tf objects. - `torch` for PyTorch support. ### Requirements for `R` functionality - The `repr` library. ### Requirements for `ipywidgets` functionality The variable inspector can also display Jupyter interactive widgets: ![ipywidgets](./ipywidgets.png) The requirements for this functionality are: - `ipywidgets` - Support for widgets in JupyterLab: `jupyter labextension install @jupyter-widgets/jupyterlab-manager` ## Install **NOTE:** The main way to install this extension is via pip as described below. ```bash pip install lckr-jupyterlab-variableinspector ``` Alternatively, one can install the extension from npmjs via: ```bash jupyter labextension install @lckr/jupyterlab_variableinspector ``` or via the extension manager that comes built-in with Jupyterlab ## Contributing ### Development install Note: You will need NodeJS to build the extension package. The `jlpm` command is JupyterLab's pinned version of [yarn](https://yarnpkg.com/) that is installed with JupyterLab. You may use `yarn` or `npm` in lieu of `jlpm` below. ```bash # Clone the repo to your local environment # Change directory to the lckr_jupyterlab_variableinspector directory # Install package in development mode pip install -e . # Link your development version of the extension with JupyterLab jupyter labextension develop . --overwrite # Rebuild extension Typescript source after making changes jlpm run build ``` You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension. ```bash # Watch the source directory in one terminal, automatically rebuilding when needed jlpm run watch # Run JupyterLab in another terminal jupyter lab ``` With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt). By default, the `jlpm run build` command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command: ```bash jupyter lab build --minimize=False ``` ### Uninstall ```bash pip uninstall lckr_jupyterlab_variableinspector ``` %package help Summary: Development documents and examples for lckr-jupyterlab-variableinspector Provides: python3-lckr-jupyterlab-variableinspector-doc %description help # jupyterlab_variableinspector ![PyPi_Version](https://img.shields.io/pypi/v/lckr-jupyterlab-variableinspector) ![Build](https://github.com/lckr/jupyterlab-variableInspector/workflows/Build/badge.svg) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/lckr/jupyterlab-variableInspector.git/master?urlpath=lab) [![GPLv3 License](https://img.shields.io/badge/License-GPL%20v3-yellow.svg)](https://opensource.org/licenses/) Jupyterlab extension that shows currently used variables and their values. Contributions in any form are welcome! ## Features ![Demogif](early_demo.gif) - Allows inspection of variables for both consoles and notebooks. - Allows inspection of matrices in a datagrid-viewer. This might not work for large matrices. - Allows an inline and interactive inspection of Jupyter Widgets. ### Supported Languages - This extension is currently targets `python` as a main language but also supports the following languages with different levels of feature completeness - `R` - `scala` via the [almond kernel](https://github.com/almond-sh/almond) ### How it Works In order to allow variabale inspection, all content that is displayed first need to be sent from the kernel to the front end. Therefore, opening large data frames with the datagrid viewer can dramatically increase your occupied memory and *significantly slow down* your browser. Use at your own risk. ## Requirements * JupyterLab >= 3.0 ### Requirements for `python` functionality - `pandas` and `numpy` are required to enable matrix inspection. - `pyspark` for spark support. - `tensorflow` and `keras` to allow inspection of tf objects. - `torch` for PyTorch support. ### Requirements for `R` functionality - The `repr` library. ### Requirements for `ipywidgets` functionality The variable inspector can also display Jupyter interactive widgets: ![ipywidgets](./ipywidgets.png) The requirements for this functionality are: - `ipywidgets` - Support for widgets in JupyterLab: `jupyter labextension install @jupyter-widgets/jupyterlab-manager` ## Install **NOTE:** The main way to install this extension is via pip as described below. ```bash pip install lckr-jupyterlab-variableinspector ``` Alternatively, one can install the extension from npmjs via: ```bash jupyter labextension install @lckr/jupyterlab_variableinspector ``` or via the extension manager that comes built-in with Jupyterlab ## Contributing ### Development install Note: You will need NodeJS to build the extension package. The `jlpm` command is JupyterLab's pinned version of [yarn](https://yarnpkg.com/) that is installed with JupyterLab. You may use `yarn` or `npm` in lieu of `jlpm` below. ```bash # Clone the repo to your local environment # Change directory to the lckr_jupyterlab_variableinspector directory # Install package in development mode pip install -e . # Link your development version of the extension with JupyterLab jupyter labextension develop . --overwrite # Rebuild extension Typescript source after making changes jlpm run build ``` You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension. ```bash # Watch the source directory in one terminal, automatically rebuilding when needed jlpm run watch # Run JupyterLab in another terminal jupyter lab ``` With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt). By default, the `jlpm run build` command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command: ```bash jupyter lab build --minimize=False ``` ### Uninstall ```bash pip uninstall lckr_jupyterlab_variableinspector ``` %prep %autosetup -n lckr-jupyterlab-variableinspector-3.0.9 %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-lckr-jupyterlab-variableinspector -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri May 05 2023 Python_Bot - 3.0.9-1 - Package Spec generated