| Name | jupyter-datainputtable JSON |
| Version |
0.8.0
JSON |
| download |
| home_page | None |
| Summary | Predefined data input tables for Jupyter notebooks |
| upload_time | 2024-07-05 18:37:37 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | BSD 3-Clause License Copyright (c) 2024, Jonathan Gutow All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
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| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
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|
# jupyter_datainputtable
<!-- Set this up once working on github
[](https://github.com/JupyterPhysSciLab/jupyter-datainputtable/actions/workflows/build.yml)
-->
Tools for generating predefined data input tables for use in Jupyter notebooks.
This is primarily for student worksheets.
TOC: [Current Features](#current-features) | [Usage](#usage) |
[Requirements](#requirements) | [Install](#install) | [Uninstall](#uninstall) |
[Contributing](#contributing)
## Current Features:
* Can create a table using the `Insert Data Entry Table` command in the
Jupyter Lab command palette.
* If using [JupyterPhysSciLab/InstructorTools](https://github.com/JupyterPhysSciLab/jupyter-instructortools)
tables can be created using an item in the "Instructor Tools" menu
(recommended usage).
* Table column and row labels can be locked once set.
* Number of rows and columns must be chosen on initial creation.
* Table will survive deletion of all cell output data.
* The code that creates the table and stores the data is not editable or
deletable by the user of the notebook unless they manually change the cell
metadata (not easily accessible in the simpler `jupyter notebook` mode rather
than `jupyter lab` mode).
* Table creation code will work without this extension installed. Tables are
viewable, but not editable in a plain vanilla Jupyter install.
* Tables include a button to create a [Pandas](https://pandas.pydata.org/)
dataframe from the table data. The code to create the dataframe is
automatically inserted into a new cell immediately below the table and run.
This cell is editable by the user.
### Wishlist:
* Add rows or columns to existing table.
## Usage:
### Create a new table using the currently selected code cell.
*NB: This will replace anything currently in the cell!*
If you are using JupyterPhysSciLab/InstructorTools and have activated the menu
select the "Insert New Data Table..." item from the menu (figure 1).
**Figure 1:** Menu item in JPSL Instructor Tools menu.
Alternatively, you can create a new table using the "Insert Data Entry Table"
command in the Jupyter Lab command pallet (figure 2).
**Figure 2:** Item in the Jupyter Lab command palette.
Either will initiate the table creation process with a dialog (figure 3).
**Figure 3:** Data table creation dialog.
### Entering and saving data
Once the table is created and you have edited and locked the column and row
labels, users can enter information in the data cells after clicking the
"Edit Data" button (figure 4). To save their edits they click the "Save
Table" button.
**Figure 4:** Data table in edit mode.
The table actions are inactive if this extension is not installed.
**Figure 5:** Data table in notebook without this extension installed.
## Requirements
- JupyterLab >= 4.0.0
- notebook >= 7.0.0
## Install
To install the extension, execute:
```bash
pip install jupyter_datainputtable
```
## Uninstall
To remove the extension, execute:
```bash
pip uninstall jupyter_datainputtable
```
## 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 jupyter_datainputtable 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 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 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 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
```
### Development uninstall
```bash
pip uninstall jupyter_datainputtable
```
In development mode, you will also need to remove the symlink created by `jupyter labextension develop`
command. To find its location, you can run `jupyter labextension list` to figure out where the `labextensions`
folder is located. Then you can remove the symlink named `jupyter-datainputtable` within that folder.
### Testing the extension (currently incomplete)
#### Frontend tests
This extension is using [Jest](https://jestjs.io/) for JavaScript code testing.
To execute them, execute:
```sh
jlpm
jlpm test
```
#### Integration tests
This extension uses [Playwright](https://playwright.dev/docs/intro) for the integration tests (aka user level tests).
More precisely, the JupyterLab helper [Galata](https://github.com/jupyterlab/jupyterlab/tree/master/galata) is used to handle testing the extension in JupyterLab.
More information are provided within the [ui-tests](./ui-tests/README.md) README.
### Packaging the extension
See [RELEASE](RELEASE.md)
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"description": "# jupyter_datainputtable\n<!-- Set this up once working on github\n[](https://github.com/JupyterPhysSciLab/jupyter-datainputtable/actions/workflows/build.yml)\n-->\nTools for generating predefined data input tables for use in Jupyter notebooks.\nThis is primarily for student worksheets.\n\nTOC: [Current Features](#current-features) | [Usage](#usage) | \n[Requirements](#requirements) | [Install](#install) | [Uninstall](#uninstall) |\n[Contributing](#contributing)\n\n## Current Features:\n\n* Can create a table using the `Insert Data Entry Table` command in the \n Jupyter Lab command palette.\n* If using [JupyterPhysSciLab/InstructorTools](https://github.com/JupyterPhysSciLab/jupyter-instructortools)\n tables can be created using an item in the \"Instructor Tools\" menu \n (recommended usage).\n* Table column and row labels can be locked once set.\n* Number of rows and columns must be chosen on initial creation.\n* Table will survive deletion of all cell output data.\n* The code that creates the table and stores the data is not editable or \n deletable by the user of the notebook unless they manually change the cell \n metadata (not easily accessible in the simpler `jupyter notebook` mode rather \n than `jupyter lab` mode).\n* Table creation code will work without this extension installed. Tables are \n viewable, but not editable in a plain vanilla Jupyter install.\n* Tables include a button to create a [Pandas](https://pandas.pydata.org/) \n dataframe from the table data. The code to create the dataframe is \n automatically inserted into a new cell immediately below the table and run.\n This cell is editable by the user.\n\n### Wishlist:\n\n* Add rows or columns to existing table.\n\n## Usage:\n### Create a new table using the currently selected code cell.\n*NB: This will replace anything currently in the cell!*\n\nIf you are using JupyterPhysSciLab/InstructorTools and have activated the menu\nselect the \"Insert New Data Table...\" item from the menu (figure 1).\n\n\n\n**Figure 1:** Menu item in JPSL Instructor Tools menu.\n\nAlternatively, you can create a new table using the \"Insert Data Entry Table\"\ncommand in the Jupyter Lab command pallet (figure 2).\n\n\n\n**Figure 2:** Item in the Jupyter Lab command palette.\n\nEither will initiate the table creation process with a dialog (figure 3).\n\n\n\n**Figure 3:** Data table creation dialog.\n### Entering and saving data\nOnce the table is created and you have edited and locked the column and row \nlabels, users can enter information in the data cells after clicking the \n\"Edit Data\" button (figure 4). To save their edits they click the \"Save \nTable\" button.\n\n\n\n**Figure 4:** Data table in edit mode.\n\nThe table actions are inactive if this extension is not installed.\n\n\n\n**Figure 5:** Data table in notebook without this extension installed.\n## Requirements\n\n- JupyterLab >= 4.0.0\n- notebook >= 7.0.0\n\n## Install\n\nTo install the extension, execute:\n\n```bash\npip install jupyter_datainputtable\n```\n\n## Uninstall\n\nTo remove the extension, execute:\n\n```bash\npip uninstall jupyter_datainputtable\n```\n\n## Contributing\n\n### Development install\n\nNote: You will need NodeJS to build the extension package.\n\nThe `jlpm` command is JupyterLab's pinned version of\n[yarn](https://yarnpkg.com/) that is installed with JupyterLab. You may use\n`yarn` or `npm` in lieu of `jlpm` below.\n\n```bash\n# Clone the repo to your local environment\n# Change directory to the jupyter_datainputtable directory\n# Install package in development mode\npip install -e \".\"\n# Link your development version of the extension with JupyterLab\njupyter labextension develop . --overwrite\n# Rebuild extension Typescript source after making changes\njlpm build\n```\n\nYou 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.\n\n```bash\n# Watch the source directory in one terminal, automatically rebuilding when needed\njlpm watch\n# Run JupyterLab in another terminal\njupyter lab\n```\n\nWith 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).\n\nBy default, the `jlpm 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:\n\n```bash\njupyter lab build --minimize=False\n```\n\n### Development uninstall\n\n```bash\npip uninstall jupyter_datainputtable\n```\n\nIn development mode, you will also need to remove the symlink created by `jupyter labextension develop`\ncommand. To find its location, you can run `jupyter labextension list` to figure out where the `labextensions`\nfolder is located. Then you can remove the symlink named `jupyter-datainputtable` within that folder.\n\n### Testing the extension (currently incomplete)\n\n#### Frontend tests\n\nThis extension is using [Jest](https://jestjs.io/) for JavaScript code testing.\n\nTo execute them, execute:\n\n```sh\njlpm\njlpm test\n```\n\n#### Integration tests\n\nThis extension uses [Playwright](https://playwright.dev/docs/intro) for the integration tests (aka user level tests).\nMore precisely, the JupyterLab helper [Galata](https://github.com/jupyterlab/jupyterlab/tree/master/galata) is used to handle testing the extension in JupyterLab.\n\nMore information are provided within the [ui-tests](./ui-tests/README.md) README.\n\n### Packaging the extension\n\nSee [RELEASE](RELEASE.md)\n",
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