| Name | chartcrafthub JSON |
| Version |
1.0.2
JSON |
| download |
| home_page | None |
| Summary | Code, debug, reuse this chart, workshop materials and more. |
| upload_time | 2024-03-23 06:52:37 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | None |
| license | MIT License Copyright (c) 2024 Artem Kislovskiy, Teresa Kubacka Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
matplotlib
visuzlization
tutorial
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Chart Craft Hub
<img src="https://raw.githubusercontent.com/Kislovskiy/ChartCraftHub/trunk/docs/source/images/logo.svg" alt="ChartCraftHub logo" width="400"/>
## Home for "Code, debug, reuse this chart" workshop materials
"Code, debug, reuse this chart" will take place on 24th of March 2024 at 09:00 at Applied Machine Learning Days 2024 in Lausanne, Switzerland.
## Installation
You can install the materials for the workshop from [PyPI](https://pypi.org/project/chartcrafthub/):
```shell
$ python3.12 -m venv .venv
$ souce .venv/bin/activate
$ python -m pip install chartcrafthub
```
The workshop materials are created with Python3.12.
## How to use
To start the workshop, just import the `chartcrafthub` package and follow the instructions:
```
(.venv) ~/d/K/ChartCraftHub ❯❯❯ python -m chartcrafthub
_____ _ _ _____ __ _ _ _ _
/ __ \ | | | / __ \ / _| | | | | | | |
| / \/ |__ __ _ _ __| |_ | / \/_ __ __ _| |_| |_ | |_| |_ _| |__
| | | '_ \ / _` | '__| __| | | | '__/ _` | _| __| | _ | | | | '_ \
| \__/\ | | | (_| | | | |_ | \__/\ | | (_| | | | |_ | | | | |_| | |_) |
\____/_| |_|\__,_|_| \__| \____/_| \__,_|_| \__| \_| |_/\__,_|_.__/
Thanks for attending "Code, debug, reuse this chart" workshop!
In this workshop, you'll learn how to:
✓ Craft visually compelling figures that enhance your document's overall appearance.
✓ Develop modular plotting functions utilizing matplotlib.
✓ Utilize Rich and debugging and method exploration.
✓ Organize your code for enhanced usability.
✓ Package your code for seamless portability.
To begin, visit the documentation home page: https://kislovskiy.github.io/ChartCraftHub/]
- Artem
Copy the great architectures. Edward Tufte
```
## Getting started
There are three ways to follow this tutorial:
* [Dev Containers](#dev-containers) if you have Docker and Visual Studio Code installed
* [GitHub Codespaces](#github-codespaces) if you don't want to install anything on your local machine
* [Local installation](#local-installation) if you are a fan of local development.
We recommend using Dev Containers or GitHub Codespaces to avoid any issues with the environment setup.
### Dev Containers
To use it, you need to have [Docker](https://www.docker.com/) and [Visual Studio Code](https://code.visualstudio.com/) installed.
This project is configured to use [devcontainer](https://code.visualstudio.com/docs/remote/containers) for development.
First, we need to install the [Remote - Containers](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers) extension in VS Code.
Then, open the project in VSCode and click on the green button in the bottom right corner of the window.
This will open a new window in a container with all the necessary tools installed.
It could take a few minutes to build the container for the first time.
Once the container is running, you'll see green "Dev Container" badge in the bottom left corner of the VSCode window.
The development environment is ready to use.
Since Docker provides an isolated environment, we don't need to create a virtual environment or install any dependencies on the host machine.
### GitHub Codespaces
If you don't want to install anything on your local machine, you could use [GitHub Codespaces](https://docs.github.com/en/codespaces/overview) throughout this tutorial.
To use it, you need to have a GitHub account and a repository forked to your account.
After that, you could open the repository in GitHub and click on the "Code" button in the top right corner of the page.
Then, select "Open with Codespaces" from the dropdown menu.
It could take a few minutes to create the environment for the first time.
Once the environment is ready, you'll see a new tab in your browser with the VSCode editor.
The development environment is ready to use.
### Local installation MacOS / Linux
If you prefer to use your local machine, you need to have Python 3.12 installed.
Create a virtual environment and install the dependencies:
```shell
$ python3 -m pip venv .venv
$ source .venv/bin/activate
$ make install
```
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"description": "# Chart Craft Hub\n\n<img src=\"https://raw.githubusercontent.com/Kislovskiy/ChartCraftHub/trunk/docs/source/images/logo.svg\" alt=\"ChartCraftHub logo\" width=\"400\"/>\n\n## Home for \"Code, debug, reuse this chart\" workshop materials\n\"Code, debug, reuse this chart\" will take place on 24th of March 2024 at 09:00 at Applied Machine Learning Days 2024 in Lausanne, Switzerland.\n\n\n\n\n## Installation\n\nYou can install the materials for the workshop from [PyPI](https://pypi.org/project/chartcrafthub/):\n\n```shell\n$ python3.12 -m venv .venv\n$ souce .venv/bin/activate\n$ python -m pip install chartcrafthub\n```\n\nThe workshop materials are created with Python3.12.\n\n## How to use\n\nTo start the workshop, just import the `chartcrafthub` package and follow the instructions:\n\n```\n(.venv) ~/d/K/ChartCraftHub \u276f\u276f\u276f python -m chartcrafthub\n \n _____ _ _ _____ __ _ _ _ _ \n / __ \\ | | | / __ \\ / _| | | | | | | | \n | / \\/ |__ __ _ _ __| |_ | / \\/_ __ __ _| |_| |_ | |_| |_ _| |__ \n | | | '_ \\ / _` | '__| __| | | | '__/ _` | _| __| | _ | | | | '_ \\ \n | \\__/\\ | | | (_| | | | |_ | \\__/\\ | | (_| | | | |_ | | | | |_| | |_) | \n \\____/_| |_|\\__,_|_| \\__| \\____/_| \\__,_|_| \\__| \\_| |_/\\__,_|_.__/ \n \n \nThanks for attending \"Code, debug, reuse this chart\" workshop! \n \nIn this workshop, you'll learn how to: \n \n\u2713 Craft visually compelling figures that enhance your document's overall appearance. \n\u2713 Develop modular plotting functions utilizing matplotlib. \n\u2713 Utilize Rich and debugging and method exploration. \n\u2713 Organize your code for enhanced usability. \n\u2713 Package your code for seamless portability.\n \nTo begin, visit the documentation home page: https://kislovskiy.github.io/ChartCraftHub/]\n \n- Artem\n \n Copy the great architectures. Edward Tufte \n```\n\n## Getting started\n\nThere are three ways to follow this tutorial:\n* [Dev Containers](#dev-containers) if you have Docker and Visual Studio Code installed\n* [GitHub Codespaces](#github-codespaces) if you don't want to install anything on your local machine\n* [Local installation](#local-installation) if you are a fan of local development.\n\nWe recommend using Dev Containers or GitHub Codespaces to avoid any issues with the environment setup.\n\n### Dev Containers\n\nTo use it, you need to have [Docker](https://www.docker.com/) and [Visual Studio Code](https://code.visualstudio.com/) installed.\nThis project is configured to use [devcontainer](https://code.visualstudio.com/docs/remote/containers) for development.\n\nFirst, we need to install the [Remote - Containers](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers) extension in VS Code.\nThen, open the project in VSCode and click on the green button in the bottom right corner of the window.\nThis will open a new window in a container with all the necessary tools installed.\nIt could take a few minutes to build the container for the first time.\n\nOnce the container is running, you'll see green \"Dev Container\" badge in the bottom left corner of the VSCode window.\nThe development environment is ready to use.\nSince Docker provides an isolated environment, we don't need to create a virtual environment or install any dependencies on the host machine.\n\n### GitHub Codespaces\n\nIf you don't want to install anything on your local machine, you could use [GitHub Codespaces](https://docs.github.com/en/codespaces/overview) throughout this tutorial.\nTo use it, you need to have a GitHub account and a repository forked to your account.\nAfter that, you could open the repository in GitHub and click on the \"Code\" button in the top right corner of the page.\nThen, select \"Open with Codespaces\" from the dropdown menu.\nIt could take a few minutes to create the environment for the first time.\n\nOnce the environment is ready, you'll see a new tab in your browser with the VSCode editor.\nThe development environment is ready to use.\n\n### Local installation MacOS / Linux\n\nIf you prefer to use your local machine, you need to have Python 3.12 installed.\nCreate a virtual environment and install the dependencies:\n\n```shell\n$ python3 -m pip venv .venv\n$ source .venv/bin/activate\n$ make install\n```\n",
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