semvec/pypi-packages huggingface dataset:
mdformat_tight_lists 0.1.1
An mdformat plugin for creating tight lists (no empty lines between list items).
Requires Python: >=3.10
Keywords: mdformat, markdown, markdown-it, formatter, lists

# mdformat-tight-lists

[![Build Status][ci-badge]][ci-link]
[![PyPI version][pypi-badge]][pypi-link]

An [mdformat](https://github.com/executablebooks/mdformat) plugin that formats Markdown lists to be tight (no empty lines between list items) following mdformat-style rules.

## Installation

```bash
pip install mdformat-tight-lists
```

Or with [pipx](https://pipx.pypa.io/) for command-line usage:

```bash
pipx install mdformat
pipx inject mdformat mdformat-tight-lists
```

## Usage

After installation, mdformat will automatically use this plugin when formatting Markdown files:

```bash
mdformat your-file.md
```

### Features

- **Smart List Formatting**: Automatically creates tight lists by removing unnecessary empty lines
- **List Type Detection**: Different top-level markers (`-`, `*`, `+`) are treated as separate lists
- **Nested List Handling**: Properly handles transitions between ordered and unordered lists
- **Multi-Paragraph Support**: Preserves loose formatting when list items contain multiple paragraphs

### Examples

**Input:**
```markdown
- Item 1

- Item 2

- Item 3
```

**Output:**
```markdown
- Item 1
- Item 2
- Item 3
```

**Multi-paragraph items (loose list preserved):**
```markdown
- First item with multiple paragraphs

  Second paragraph of first item

- Second item
```

## Development

### Setup

```bash
# Clone the repository
git clone https://github.com/jdmonaco/mdformat-tight-lists.git
cd mdformat-tight-lists

# Install development environment with uv
uv sync
```

### Running Tests

```bash
# Run all tests
uv run pytest

# Run with coverage
uv run pytest --cov=mdformat_tight_lists

# Run tests verbosely
uv run pytest -v
```

### Adding Tests

To add new test cases, edit `tests/fixtures.md` following the existing format:
- Test title
- Input markdown (between dots)
- Expected output (between dots)

## License

MIT - see LICENSE file for details.

[ci-badge]: https://github.com/jdmonaco/mdformat-tight-lists/workflows/CI/badge.svg
[ci-link]: https://github.com/jdmonaco/mdformat-tight-lists/actions?query=workflow%3ACI+branch%3Amain+event%3Apush
[pypi-badge]: https://img.shields.io/pypi/v/mdformat-tight-lists.svg
[pypi-link]: https://pypi.org/project/mdformat-tight-lists
proceed 0.0.11
Execute pipelines based on files and containers.
Requires Python: >=3.11

# Proceed
Declarative file processing with YAML and containers.

**Proceed** is a Python library and CLI tool for declarative batch processing.
It reads a **pipeline** specification declared in [YAML](https://yaml.org/).
A pipeline contains a list of **steps** that are based on [Docker](https://www.docker.com/) images and containers.

Each pipeline execution accepts values for declared **args**, allowing controlled, explicit configuration of steps at runtime.
Each execution produces an **execution record** that accounts for accepted arg values, step logs, and checksums of input and output files.

Hopefully, Proceed will allow you to express everything you need to know about your processing pipeline in a *"nothing up my sleeves"* way.  The pipeline specification should be complete enough to share with others who have Proceed and Docker installed.
The execution record should allow for auditing of expected outcomes and reproducibility.

## docs
Here are the [main docs](https://benjamin-heasly.github.io/proceed/index.html) for Proceed.

# Installation
Proceed requires [Python](https://www.python.org/) and [Docker](https://www.docker.com/) to be installed.
With those, it should be able to run a wide variety pipelines and steps via containers.

## pip
Proceed itself is available on [PyPI](https://pypi.org/project/proceed/).
This is the recommended way to install Proceed:

```
$ pip install proceed
```

## git and pip
You can also install Proceed from source.

```
$ pip install git+https://https://github.com/benjamin-heasly/proceed.git

# editable mode
$ git checkout https://github.com/benjamin-heasly/proceed.git
$ pip install -e ./proceed
```

## check installation
You can check if Proceed installed correctly using the `proceed` command.

```
$ proceed --version
Proceed x.y.z

$ proceed --help
usage etc...
```

## development and testing

You can set up a development environment with [conda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html) and [dev-environment.yml](./dev-environment.yml).

```
conda env create -f dev-environment.yml
# or
conda env update -f dev-environment.yml
```

With that, you should be able to run through the Proceed unit and integration tests.

```
conda activate proceed-dev
hatch run test:cov
```
gensarpy 0.1.2
A Python library for testing the convergence of mathematical series.
Requires Python: >=3.6

# gensarpy

A Python library for testing the convergence of mathematical series.

## Installation

```bash
pip install gensarpy
```

## Usage

```python
from gensarpy.convergence_tests import check_convergence

# Test a convergent series
result = check_convergence('1/n**2')
print(result)  # Output: Convergent by the P-Series Test

# Test a divergent series
result = check_convergence('1/n')
print(result)  # Output: Divergent by the P-Series Test
```