semvec/pypi-packages huggingface dataset:
GameBox 0.10.0.dev1
GameBox is a beginner-friendly Python package built on top of pygame, designed to make 2D game development faster and easier. It provides ready-to-use modules, utilities, and abstractions that let new developers create polished games without needing advanced coding knowledge—while still offering the flexibility for experienced coders to customize and extend.
Requires Python: >=3.9

GameBox is a lightweight 2D game framework built on pygame.
This is an early technical preview of a full engine rewrite.
APIs may change frequently.

github: https://github.com/sfertig/GameBox

Versioning
GameBox follows a modified semantic versioning scheme.
Versions starting with 0.x.x are experimental and may change without notice.
Stable, marketed releases will begin at 1.0.0.
jibberish-to-hebrew-mcp 0.1.0
MCP server: convert QWERTY gibberish to Hebrew and vice versa by keyboard layout mapping
Requires Python: >=3.10

# jibberish-to-hebrew-mcp

MCP server that converts text between “gibberish” English and Hebrew by swapping characters according to the **QWERTY ↔ Hebrew (SI 1452)** keyboard layout.

## Tools

- **qwerty_to_hebrew_text** — Converts English-looking gibberish (typed with Hebrew in mind but keyboard set to English) to Hebrew.
- **hebrew_to_qwerty_text** — Converts Hebrew text to the equivalent QWERTY key sequence.

## Install and run

```bash
pip install jibberish-to-hebrew-mcp
jibberish-to-hebrew-mcp
```

Or with [uv](https://github.com/astral-sh/uv):

```bash
uvx jibberish-to-hebrew-mcp
```

## Cursor / Claude config

Add to your MCP config (e.g. `~/.cursor/mcp.json`):

```json
{
  "mcpServers": {
    "jibberish-to-hebrew": {
      "command": "jibberish-to-hebrew-mcp",
      "args": []
    }
  }
}
```

If the command is not on PATH, use the full path to the script or `uvx jibberish-to-hebrew-mcp` (with `"command": "uvx"`, `"args": ["jibberish-to-hebrew-mcp"]`).

---

### MCP Registry (optional)

To publish this server to the [official MCP Registry](https://modelcontextprotocol.io/registry/quickstart), the README must contain the server name below (used for ownership verification). <!-- mcp-name: io.github.Maor-Ar/jibberish-to-hebrew -->
Topsis-Satyam-102303729 1.0.1
Implementation of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)
Requires Python: >=3.8

*TOPSIS* (Technique for Order Preference by Similarity to Ideal Solution) is a multi-criteria decision analysis method.

## Installation

bash
pip install Topsis-Satyam-102303729


## Usage

### Command Line

bash
topsis <input_file> <weights> <impacts> <output_file>


### Parameters

- *input_file*: Path to input CSV file
- *weights*: Comma-separated weights (e.g., "1,1,1,2")
- *impacts*: Comma-separated impacts, either + or - (e.g., "+,+,-,+")
- *output_file*: Path to output CSV file

### Example

bash
topsis-satyam data.csv "1,1,1,1,1" "+,+,+,+,+" output.csv



### Input File Format

The input CSV file should have:
- First column: Object/item names
- Remaining columns: Criteria values (numeric)

Example:

Model,Price,Storage,Camera,Looks
M1,250,16,12,5
M2,200,16,8,3
M3,300,32,16,4


### Output

The output file will contain:
- All original columns
- *Topsis Score*: Calculated TOPSIS score
- *Rank*: Rank based on TOPSIS score

## Requirements

- Python >= 3.8
- pandas >= 1.0.1
- numpy >= 1.18.0

## License

MIT License

## Author

Satyam Gupta

## Links

-GitHub: https://github.com/sat-yam-12/TOPSIS-SATYAM-102303729
modelcraft 6.0.0
Automated model-building pipeline for X-ray crystallography and cryo-EM
Requires Python: >=3.9

![](https://github.com/paulsbond/modelcraft/blob/691b8a0d72dbf48b8d8a431bdb193298a397e1bb/modelcraft.png)

# ModelCraft

ModelCraft is an automated model-building pipeline
that builds proteins and nucleic acids
into X-ray crystallography and cryo-EM maps.
It combines the previous Buccaneer and Nautilus pipelines and adds new steps
for density modification, refinement, validation and pruning.

## Installation

ModelCraft is distributed with CCP4.
Please obtain the latest version from the
[CCP4 download page](https://www.ccp4.ac.uk/download).

## Graphical interfaces

For X-ray crystallography, ModelCraft can be used through
[CCP4i2](https://ccp4i2.gitlab.io/rstdocs/tasks/modelcraft/index.html) or
[CCP4 Cloud](https://cloud.ccp4.ac.uk/manuals/html-taskref/doc.task.ModelCraft.html).
For cryo-EM, it is available in
[CCP-EM Doppio](https://www.ccpem.ac.uk/docs/doppio/user_guide.html).

## Command-line interface

The first argument must be either
`xray` for X-ray crystallography or `em` for cryo-EM SPA.
The command line documentation has detailed information on individual arguments.

```bash
modelcraft xray --help
```

```bash
modelcraft em --help
```

## Links

- [Source (latest)](https://github.com/paulsbond/modelcraft)
- [Source (releases)](https://github.com/paulsbond/modelcraft/releases)
- [Issues (e.g. bugs and feature requests)](https://github.com/paulsbond/modelcraft/issues)
- [PyPI (Python Package Index)](https://pypi.org/project/modelcraft)

## Citations

- [ModelCraft](https://doi.org/10.1107/S2059798322007732)
- [Buccaneer](https://doi.org/10.1107/S0907444906022116)
- [EMDA](https://doi.org/10.1016/j.jsb.2021.107826)
- [Nautilus](https://doi.org/10.1107/S2052252514019290)
- [Parrot](https://doi.org/10.1107/S090744490903947X)
- [Refmac](https://doi.org/10.1107/S2059798318000979)
- [Servalcat](https://doi.org/10.1107/S2059798321009475)
- [Sheetbend](https://doi.org/10.1107/S2059798320013170)