semvec/pypi-packages huggingface dataset:
pymergetic-core 0.0.7.post1.dev0
Core package for PymergeticOS with optional feature groups
Requires Python: >=3.11
Keywords: pymergetic, core, os

# Pymergetic Core

Core package for PymergeticOS with optional feature groups organized by topic.

## Installation

### Base Package

```bash
pip install pymergetic-core
```

### With Optional Dependencies

```bash
# Install with console features (CLI tools)
pip install pymergetic-core[console]

# Install with config features (configuration management)
pip install pymergetic-core[config]

# Install with multiple extras
pip install pymergetic-core[console,config]
```

## Optional Dependencies (Extras)

- **console**: Virtual console and CLI package dependencies
  - `fire>=0.5.0` - Python Fire for CLI interfaces
  - `rich>=13.0.0` - Rich text and beautiful formatting for terminal

- **config**: Configuration management dependencies
  - `pydantic>=2.0.0` - Data validation using Python type annotations
  - `pydantic-settings>=2.0.0` - Settings management using Pydantic
  - `pyyaml>=6.0` - YAML parser and emitter

## Development

### Building and Publishing

```bash
# Build package
make build

# Publish to PyPI
make publish

# Full release (tag, build, publish)
make release
```

See `Makefile` for all available targets.
audity 0.12.0
Audit, inspect, and survey data from the terminal.
Requires Python: >=3.10

# Audity
Audit, inspect, and survey data by generating visuals with matplotlib on the fly. Audity is a CLI tool that loads a data file (csv/xlsx) a offers charting options allowing you to chose x and y axis. Visuals are rendered in a new window and all data manipulation is in memory. 

# Usage
Just run `audity` in the directory of your data file(s). File selection is handled within audity. Simply use the arrow keys and enter on your desired file. Audity will then load the file as a Pandas Dataframe and then the fun begins.

# Features
- Directory navigation for file selection
- Preview or describe Dataframes
- Edit column names
- Edit column data types
- Remove columns
- Remove outliers (IQR)
- Render charts (see [Supported Visuals](#Supported-Visuals) below)

# Supported Visuals
- Box Plot
- Violin Plot
- Line Plot
- Bar Plot
- Scatter Plot
- Joint Grid Plot
- Relation Plot
- Pair Plot