semvec/pypi-packages huggingface dataset:
papiry 0.1.1
Tool for organizing and downloading research papers.
License: MIT
Requires Python: <4.0,>=3.11

# Paper Downloader 📜

This repository provides a simple tool for downloading free scientific papers based on a structured
index of papers stored in `index.md`. The repository contains the following files:

## ✨ Features

- 💾 Download papers from URLs specified in `index.md`.
- 🗂️ Organize downloaded papers into folders based on categories.
- ⚡ Easy-to-use and lightweight tool for researchers and students.

## 🚀 Getting Started 

### Prerequisites

Ensure you have a reasonable version of Python installed on your system.

### Installation

1. Clone the repository:

   ```bash
   git clone https://github.com/Kripner/papiry
   cd papiry
   ```

2. Install the required dependencies:

   ```bash
   pip install -r requirements.txt
   ```

### Usage

1. Update the `index.md` file to include the papers you want to download. The format of `index.md` is as follows:

   ```markdown
   # [CategoryName] Optional description

   - [PaperName] Paper Title: <URL>
   ```

   Example:

   ```markdown
   # [games] Two-player zero-sum games

   - [AlphaGoZero] Mastering the game of Go without human knowledge: https://ics.uci.edu/~dechter/courses/ics-295/winter-2018/papers/nature-go.pdf
   - [AlphaZero] Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm: https://arxiv.org/abs/1712.01815
   ```

2. Run the `download.py` script:

   ```bash
   python download.py
   ```

3. The script will create a folder for each category and download the corresponding papers into the respective folders.

## Example

Given the following `index.md`:

```markdown
# [games] Two-player zero-sum games

- [AlphaGoZero] Mastering the game of Go without human knowledge: https://ics.uci.edu/~dechter/courses/ics-295/winter-2018/papers/nature-go.pdf
- [AlphaZero] Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm: https://arxiv.org/abs/1712.01815
```

Running the script will create the following folder structure:

```
output/
├── games/
   ├── AlphaGoZero.pdf
   └── AlphaZero.pdf
```

## Contributing

Contributions are welcome! Please submit a pull request or open an issue to discuss potential improvements.
dcegm 0.1.0
Python implementation of the DC-EGM algorithm from Iskhakov, Jorgensen, Rust, and Schjerning (QE, 2017).
License: MIT
Requires Python: >=3.10
Keywords: Computational Economics, DC-EGM, Dynamic Programming, Econometrics, Economics, Life Cycle Models, Statistics

# DC-EGM

[![Continuous Integration Workflow](https://github.com/OpenSourceEconomics/dcegm/actions/workflows/main.yml/badge.svg)](https://github.com/OpenSourceEconomics/dcegm/actions/workflows/main.yml)
[![Codecov](https://codecov.io/gh/OpenSourceEconomics/dcegm/branch/main/graph/badge.svg)](https://app.codecov.io/gh/OpenSourceEconomics/dcegm)
[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/OpenSourceEconomics/dcegm/main.svg)](https://results.pre-commit.ci/latest/github/OpenSourceEconomics/dcegm/main)
[![Black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

Python implementation of the Discrete-Continuous Endogenous Grid Method (DC-EGM) for
solving dynamic stochastic lifecycle models of continuous (e.g. consumption-savings) and
additional discrete choices.

The solution algorithm employs an extension of the Fast Upper-Envelope Scan (FUES) from
Dobrescu & Shanker (2022).

## References

1. Iskhakov, Jorgensen, Rust, & Schjerning (2017).
   [The Endogenous Grid Method for Discrete-Continuous Dynamic Choice Models with (or without) Taste Shocks](http://onlinelibrary.wiley.com/doi/10.3982/QE643/full).
   *Quantitative Economics*
1. Christopher D. Carroll (2006).
   [The method of endogenous gridpoints for solving dynamic stochastic optimization problems](http://www.sciencedirect.com/science/article/pii/S0165176505003368).
   *Economics Letters*
1. Loretti I. Dobrescu & Akshay Shanker (2022).
   [Fast Upper-Envelope Scan for Discrete-Continuous Dynamic Programming](https://dx.doi.org/10.2139/ssrn.4181302).
sqlmate 0.0.1
A simple SQL utility package
License: MIT
Requires Python: >=3.8

# SQLMate

A simple SQL utility package for Python.

## Installation

```bash
pip install sqlmate
```

## Usage

### Check Version

```python
import sqlmate
print(sqlmate.__version__)
```

Or use the command line:

```bash
sqlmate --version
```

## Features

- Version query functionality
- More features coming soon...

## License

MIT License