semvec/pypi-packages huggingface dataset:
dataiter 1.2
Simple, light-weight data frames for Python
License: MIT
Requires Python: >=3.9.0

Simple, Light-Weight Data Frames for Python
===========================================

[![PyPI](https://img.shields.io/pypi/v/dataiter.svg)](https://pypi.org/project/dataiter)
[![Downloads](https://pepy.tech/badge/dataiter/month)](https://pepy.tech/project/dataiter)

Dataiter's **`DataFrame`** is a class for tabular data similar to R's
`data.frame`, implementing all common operations to manipulate data. It
is under the hood a dictionary of NumPy arrays and thus capable of fast
vectorized operations. You can consider it to be a light-weight
alternative to Pandas with a simple and consistent API. Performance-wise
Dataiter relies on NumPy and Numba and is likely to be at best
comparable to Pandas.

## Installation

```bash
# Latest stable version
pip install -U dataiter

# Latest development version
pip install -U git+https://github.com/otsaloma/dataiter

# Numba (optional)
pip install -U numba
```

Dataiter optionally uses **Numba** to speed up certain operations. If
you have Numba installed, Dataiter will use it automatically. It's
currently not a hard dependency, so you need to install it separately.

## Quick Start

```python
>>> import dataiter as di
>>> data = di.read_csv("data/listings.csv")
>>> data.filter(hood="Manhattan", guests=2).sort(price=1).head()
.
        id      hood zipcode guests    sqft price
     int64    string  string  int64 float64 int64
  ──────── ───────── ─────── ────── ─────── ─────
0 42279170 Manhattan   10013      2     nan     0
1 42384530 Manhattan   10036      2     nan     0
2 18835820 Manhattan   10021      2     nan    10
3 20171179 Manhattan   10027      2     nan    10
4 14858544 Manhattan              2     nan    15
5 31397084 Manhattan   10002      2     nan    19
6 22289683 Manhattan   10031      2     nan    20
7  7760204 Manhattan   10040      2     nan    22
8 43292527 Manhattan   10033      2     nan    22
9 43268040 Manhattan   10033      2     nan    23
.
```

## Documentation

https://dataiter.readthedocs.io/

If you're familiar with either dplyr (R) or Pandas (Python), the
comparison table in the documentation will give you a quick overview of
the differences and similarities in common operations.

https://dataiter.readthedocs.io/en/stable/comparison.html

## Development

To install a virtualenv for development, use

    make venv

or, for a specific Python version

    make PYTHON=python3.X venv
char-counter-alexxstep 0.1.0
Count unique characters in text or files
License: MIT
Requires Python: >=3.8
Keywords: characters, cli, counter, text

# Char Counter

A Python CLI tool and library for counting unique characters in text strings or files.

## Features

- ✅ Count unique characters in text strings
- ✅ Process text files
- ✅ Priority system: `--file` takes precedence over `--string`
- ✅ Comprehensive error handling
- ✅ Can be used as CLI tool or Python library

## Installation

```bash
pip install char-counter-alexxstep
```

## Usage

### Command Line Interface

Count unique characters in a string:

```bash
char-counter --string "abbbccdf"
# Output: 3
```

Count unique characters from a file:

```bash
char-counter --file path/to/file.txt
```

Priority rule - if both arguments provided, file takes precedence:

```bash
char-counter --string "ignored" --file data.txt
# Processes the file, ignores the string argument
```

### As Python Library

```python
from char_counter import count_unique_characters

# Count unique characters
result = count_unique_characters("abbbccdf")
print(result)  # Output: 3

# Characters that appear exactly once: a, d, f
```

### What are "unique characters"?

A character is considered **unique** if it appears **exactly once** in the text.

**Examples:**

- `"abbbccdf"` → 3 unique characters (a, d, f)
- `"aabbcc"` → 0 unique characters (all repeat)
- `"abc"` → 3 unique characters (all unique)

## Development

### Installation for Development

```bash
# Clone the repository
git clone https://git.foxminded.ua/python-web/task5_create_package.git
cd task5_create_package

# Install in editable mode with dev dependencies
pip install -e ".[dev]"
```

### Running Tests

```bash
# Run all tests
python -m pytest tests/ -v

# Run with coverage
python -m pytest tests/ --cov=char_counter --cov-report=html
```

### Code Quality

This project uses `ruff` for linting and formatting:

```bash
# Format code
uvx ruff format .

# Check and fix linting issues
uvx ruff check . --fix
```

## Requirements

- Python 3.8 or higher
- No external dependencies for core functionality

## License

MIT License - see LICENSE file for details.

## Author

Oleksiy Stypanets (Alex Step)

## Project Structure

```
task5_create_package/
├── src/
│   └── char_counter/
│       ├── __init__.py      # Package initialization
│       ├── counter.py       # Core counting logic
│       └── cli.py           # Command-line interface
├── tests/
│   ├── test_counter.py      # Unit tests for counter
│   └── test_cli.py          # Tests for CLI with mocks
├── pyproject.toml           # Project configuration
├── README.md                # This file
└── LICENSE                  # MIT License
```
cutstitch 0.2.0
A tool to stitch images together using various cutout modes.
License: MIT
Requires Python: >=3.12
Keywords: image, stitch, cutout, cli, tool

# cutstitch

A tool to stitch images together using various cutout modes.

## Usage

### CLI

```
usage: cutstitch [-h] [--mode {vertical,horizontal,diagonal,circle}] [--angle ANGLE] [--output OUTPUT] files [files ...]

positional arguments:
  files                 Image files to stitch together (two or more, in order)

options:
  -h, --help            show this help message and exit
  --mode {vertical,horizontal,diagonal,circle}
                        Cutout mode (default: vertical)
  --angle ANGLE         Angle for diagonal mode
  --output OUTPUT       Output file name
```

#### Examples
```sh
cutstitch image1.png image2.png --mode vertical --output result.png
```

## Features
- Stitch multiple images together
- Multiple  cutout modes
- Simple CLI
tycho.nexus 0.0.14
The official Python API wrapper for Nexus, by Tycho
License: MIT
Requires Python: >=3.8
Keywords: nexus, tycho

The official Python API wrapper for Nexus, by Tycho.  
It provides a convenient way to interact with Nexus APIs.

### 📖 [Documentation](https://github.com/TychoTeam/nexus-py/wiki) | [PyPI](https://pypi.org/project/tycho.nexus)

## Features

- **Full Coverage**  
  Supports all features from the API.
- **Maintained**  
  Actively maintained and fully open source for any contributions.
- **Rate Limits**  
  By default, the package handles and queues requests to ensure **near-zero** chances of rate limits.
- **Well Typed**  
  The package is strictly typed and all API data is transformed for ease of use.

#### Check out the documentation for all details.

## Install Latest Release (`pip`)

```sh
pip install tycho.nexus
```

The package has been tested for Python `v3.8+`. It may not work on older versions.