Metadata-Version: 2.1
Name: vizblend
Version: 1.0.0
Summary: A Python package to generate HTML reports from Plotly figures using Jinja2 templates.
Home-page: https://github.com/MahmoudHousam/VizBlend
Author: Mahmoud Housam
Author-email: mahmoudhousam60@gmail.com
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: plotly==5.24.1
Requires-Dist: black==24.10.0
Requires-Dist: pytest==8.3.4
Requires-Dist: pandas==2.2.3
Requires-Dist: jinja2==3.1.4
Requires-Dist: bs4==0.0.2

# VizBlend

VizBlend is a Python package that simplifies the process of creating interactive analytical reports by consolidating Plotly figures into a single HTML file. It’s designed to function like a modern PowerPoint presentation but with the power of stunning and interactive data visualizations.

Whether you’re a data analyst, scientist, or developer, VizBlend streamlines the visualization workflow and enhances collaboration.

# Demo
Below is a preview of a report generated with VizBlend:

![VizBlend Thumbnail](demo/demo.gif)

# Installation

Install vizBlend using pip:
```
pip install vizBlend
```

# Learning Purpose

Besides its main job, this repo intends to teach aspiring data analysts or even data scientists who cannot have full control over their coding cycle. With a simple mission: create visualizations and append them in one interactive report, you can take your learning curve up to include useful skills:
* Write unit and integration tests with edge cases to ensure your code is not error-prone.

* Write CI/CD workflows to run on every push or pull request to ensure the newly committed code is compatible enough.

* Creating, managing and deploying your packaged code to PyPi so that you can simply run `pip install <package_name>` and start using it.


    ##### Useful Resources

    These are the resources that helped this work appear
    * [GitHub Actions for Python Packages: How to Automate Releases to PyPi](https://www.youtube.com/watch?v=NMQwzI9hprg&ab_channel=ArjanCodes)
  
    * [Automated Python Unit Testing Made Easy with Pytest and GitHub Actions](https://pytest-with-eric.com/integrations/pytest-github-actions/)

    * [Building and testing Python | Official GitHub Actions Docs](https://docs.github.com/en/actions/use-cases-and-examples/building-and-testing/building-and-testing-python)
