semvec/pypi-packages huggingface dataset:
magento-dump 1.0.33
Magento Database Code end Media Dump & Table Analyzer Tool
Requires Python: >=3.6

# Magento Database Management Tool
A powerful Python script to list Magento database tables and perform MySQL dumps with filtering and compression.

# Features
✅ Show Table Sizes: Lists only tables larger than 1MB, sorted by size.</br>
✅ Dump Full Database: Dumps all tables, ignoring predefined ones.</br>
✅ Interactive CLI: Select options using an interactive menu.</br>
✅ Progress Tracking: Shows real-time progress during MySQL dump.</br>
✅ Config Auto-Detection: Reads Magento env.php for database settings.</br>
✅ Compression: Dumps are gzip compressed for storage efficiency.</br>

# Installation
1. Clone the Repository

```
git clone https://github.com/yourusername/magento-db-tool.git
cd magento-db-tool
```
2. Install Dependencies

```
pip install tqdm simple-term-menu
```
🔹 Run Interactive CLI
```
python3 magento_db_tool.py
```
🔹 Show Tables Bigger Than 1MB
```
python3 magento_db_tool.py show-tables
```
🔹 Dump Entire Magento Database
```
python3 magento_db_tool.py db-dump
```
📝 Commands Overview
Command	Description
- show-tables	List tables larger than 1MB with row count & size
- db-dump	Dumps all tables with gzip compression
- exit	Close the tool
📦 Example Output
Listing Tables

🔍 Fetching table details (only tables > 1MB)...
```
Table Name                            Rows           Size (MB)  
=================================================================
sales_order                           50000         15.6  
catalog_product_entity                120000        12.3  
customer_entity                        30000         8.4  
```
✅ Showing 3 tables larger than 1MB.
Dumping Database
```
🚀 Starting database dump...
📂 Dumping table: sales_order ...
📂 Dumping table: catalog_product_entity ...
📂 Dumping table: customer_entity ...

✅ Database dump successful: magento_luma_dump_20240219.sql.gz
```
🔧 Configuration
This tool automatically extracts your Magento database settings from app/etc/env.php. No manual setup required!

Change ignored tables in ignore_tables inside the script.
⏱ Automate with CRON
To schedule daily database backups at midnight, add this to crontab -e:

```
0 0 * * * /usr/bin/python3 /path/to/magento_db_tool.py db-dump
```

## Deploy to PyPI, follow these steps:

1️. Install Twine (if not installed)
```
pip install twine
```

2️. Build the Package
Inside your project root (magento-dump/):

```
pip install --upgrade setuptools
python setup.py sdist bdist_wheel
```

3️. Upload to PyPI
```
twine upload dist/*
```
or
```
rm -rf dist/ && python setup.py sdist bdist_wheel && twine upload dist/*
```
or new wey:
```
pip install build
rm -rf dist/*
python -m build
pip install twine
twine upload dist/*
```
This will ask for your PyPI credentials. Once uploaded, you can install your package with:

```
pip install magento-dump
```

📜 License
MIT License. Free to use and modify.
platon 6.3
A package to compute transmission spectra and retrieve atmospheric parameters from transmission spectra

# PLanetary Atmospheric Transmission for Observer Noobs
<img src="logo.png" height="315">

 [![codecov](https://codecov.io/gh/ideasrule/platon/branch/devel/graph/badge.svg)](https://codecov.io/gh/ideasrule/platon)
[![arXiv](http://img.shields.io/badge/arXiv-2004.09513-orange.svg)](https://arxiv.org/abs/2004.09513) 
[![arXiv](http://img.shields.io/badge/arXiv-1811.11761-orange.svg)](https://arxiv.org/abs/1811.11761)

**Feb 24, 2025: PLATON v6.3 is out!  The main difference from v6.2 is that we now include realistic emission from rocky surfaces using the emissivity library from [Paragas et al 2025](https://arxiv.org/abs/2502.04433).  The library contains 11 mineral compositions across 3 surface textures, and were obtained via lab reflectance measurements.**

**Oct 30, 2024: PLATON v6.2 is out, with major updates!  This corresponds most closely to the version described in [Zhang et al 2024](https://arxiv.org/abs/2410.22398).  Major changes include GPU support, free retrievals, surface emission, higher-resolution (R=20k) and more up-to-date opacities, leave-one-out cross-validation, pymultinest, and much better plotting tools.**

**February 2, 2020: PLEASE re-clone your repository if you cloned it before this
date!  On this date, all data files were deleted from the repository, including
from its history.  This shrank the repository's size from 1.2 GB to 36 MB,
which respects GitHub's size limit.**

**November 29, 2018: PLATON v3.0 is out!  Please check the release notes on GitHub for the list of new features.  Our paper actually describes v2.1, but v3 has a substantial number of improvements, and we strongly recommend everyone use it.**

**NEW (October 1): Version 2 is out, with a huge number of changes! Make sure to check out the release notes, and upgrade.**

PLATON is a fast and easy to use forward modelling and retrieval tool for
exoplanet atmospheres. It was written by Michael Zhang and Yayaati Chachan, and
is based on ExoTransmit by Eliza Kempton.

We welcome any feedback. Please send any comments, suggestions, or bug reports
to Michael Zhang: zmzhang "at" caltech.edu
**
To find installation instructions and quickstart examples, read the
documentation at: https://platon.readthedocs.io

*Now, these points of data  
make a beautiful line  
And we're out of beta  
We're releasing on time!*
black-hole-gui 0.0.0.dev1
A framework for creating data analysis GUIs that absorb all data within their event horizon.
Requires Python: >=3.10

<h1 align="center">
<img src="https://github.com/Grant-Giesbrecht/graf/blob/main/docs/images/graf_banner.png?raw=True" width="800">
</h1><br>

## So what is it?
GrAF is a file format which allows you to save graphs, including the data and format settings. 

## Where does this fit compared to other formats?

There are certainly other formats for saving graphs. One on end of the spectrum, you have 'visual' mechanisms for storing the graph such as PNGs or other bitmap formats. These formats guarantee an accurate representation of your graph, including perfect representation of the styling, however it does not contain the raw data. If you want to access the data later, you'll have to visually infer what the points are.

On the other end of the spectrum, you have the GrAF format. GrAF does not guarantee that the graph will look _exactly_ the same; fonts, line sizes, etc can vary between platforms. However, the core promise of GrAF is that the key aspects of the graph for scientific communication _will_ be retained. The data will be saved as a list of floats in a way that's easy to access, and formatting parameters critical to the visual language of data expression such as graph limits, line types and marker selection, will all be retained. In other words, the data will be accessible, the message of the graph will be preserved, and the formatting can be easily adjusted to match your needs of the day. You can open multiple graf files from previous publications and quickly restyle them to offer a cohesive theme for a new presentation. Or you can quickly merge the data from multiple plots into one, or change the plot type to better convey your point. 

(Mention how SVG sits inbetween bitmaps and GrAF; preserves formatting kinda, is editable, but loses the data.)
(Mention how Pickled figs are great in Python (perfect formatting and data!) but are complex to access due to their formatting sophistication and cannot easily be read in other languages )
(Mention how MATLAB figs are similar to Pklfigs in that they have perfect formatting and store data, but once again, are not easily cross platform and so complex quickly merging files is not trivial. )

(TODO: Add a function to spit out the X and Y data as variables in ipython and/or print to screen.)

The key promise of GrAF is that it will retain the graph data in a way that's easy to access