semvec/pypi-packages huggingface dataset:
abatcher 0.2.0
Parallel HTTP request batcher with rate limiting, retries, connection pooling, and more.
Requires Python: >=3.12

# `abatcher`

Simple parallel HTTP request batcher with rate limiting, retries, connection pooling, and more. The entire API is only 1 function.

## 🛠️ Usage

Using abatcher should be as simple as:

```python
import abatcher

requests = [
    # Simple URL GET request
    "https://httpbin.org/anything",
    # Custom request
    {
        "url": "https://httpbin.org/post",
        "method": "POST",
        "params": {"name": "Test"},
        "headers": {"X-Custom": "value"},
    },
]

results = abatcher.run(requests)

print(f"Batch requests results: {results}")
```

If you need more control, you can also send a custom client.

```python
import httpx
import abatcher

custom_client = httpx.AsyncClient(
    auth=("user", "pass"),
    timeout=httpx.Timeout(45.0),
    limits=httpx.Limits(max_connections=100, max_keepalive_connections=20),
)

results = abatcher.run(
    requests,
    client=custom_client,
    max_concurrent=20,
    max_per_second=10,
    cache=True,
    cache_dir="custom_cache",
    cache_ttl=3600,
)

print(f"Batch requests results: {results}")

```
textmeld 0.3.0
A tool to combine multiple text files into one for LLM training and prompts
Requires Python: <4.0,>=3.10

# TextMeld
A CLI tool to combine text files into one. Perfect for preparing LLM training data and prompt engineering.

## Features
- Combine multiple text files into a single file
- Automatic recognition of .gitignore patterns
- Automatic skipping of binary files and hidden files
- Option to limit output character count
- Flexible file exclusion patterns

## Installation
```bash
pip install textmeld
```

Using Poetry:
```bash
poetry add textmeld
```

## Usage
### Basic Usage
```bash
# Basic usage (outputs to stdout)
textmeld /path/to/your/directory
# Specify output file
textmeld /path/to/your/directory -o output.txt
# Limit maximum character count
textmeld /path/to/your/directory --max-chars 100000
```

### Available Options
```
usage: textmeld [-h] [-o OUTPUT] [-e EXCLUDE] [-m MAX_CHARS] directory
A tool to merge multiple text files into one file
positional arguments:
  directory             Target directory path
options:
  -h, --help            Show help message and exit
  -o OUTPUT, --output OUTPUT
                        Output file path (if not specified, outputs to stdout)
  -e EXCLUDE, --exclude EXCLUDE
                        File patterns to exclude (can specify multiple)
  -m MAX_CHARS, --max-chars MAX_CHARS
                        Maximum character count for output
```

### Using Exclusion Patterns
To exclude specific files or directories:
```bash
# Exclude specific extensions
textmeld /path/to/your/directory -e "*.log" -e "*.tmp"
# Exclude specific directories
textmeld /path/to/your/directory -e "node_modules/" -e "venv/"
```

## Output Format
TextMeld's output consists of two parts:
1. **Directory Structure**: A tree view of the target directory
2. **Merged Content**: Combined contents of all text files (each file has a header)
```
Directory Structure:
====================
└── project/
    ├── README.md
    ├── main.py
    └── utils/
        └── helper.py
Merged Content:
====================
==========
File: project/README.md
==========
# Project Documentation
...
==========
File: project/main.py
==========
def main():
    print("Hello World")
...
==========
File: project/utils/helper.py
==========
def helper_function():
    return True
...
```

## Supported File Formats
TextMeld automatically detects text files. Generally supported file formats include:
- Markdown (.md)
- Text (.txt)
- YAML (.yaml, .yml)
- JSON (.json)
- Python (.py)
- JavaScript (.js)
- TypeScript (.ts)
- JSX/TSX (.jsx, .tsx)
- HTML (.html)
- CSS (.css)
- Other text-based file formats

## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
macos-clipboard-mcp 1.0.2
A simple utility that provides model context protocol (MCP) tools for interacting with the macOS clipboard.
Requires Python: >=3.12

# MacOS Clipboard MCP

A simple utility that provides model context protocol (MCP) tools for interacting with the macOS clipboard.

## Features

- Copy text to the clipboard
- Paste text from the clipboard
- Paste images from the clipboard (supports TIFF, PNG, and JPEG formats)

## mcp config


### method1(recommended)
```json
{
    "clipboard": {
        "command": "uvx",
        "args": [
            "macos-clipboard-mcp"
        ]
    }
}
```

### method2

```json
{
    "clipboard": {
            "command": "uv",
            "args": [
                "--directory",
                "<your-local-folder>/macos-clipboard-mcp",
                "run",
                "main.py"
            ]
        }
}
```


## Installation

```bash
uv sync
python main.py
```

## Requirements

- Python 3.12+
- macOS (uses AppleScript for clipboard operations)

## Usage

Start the MCP server:

```bash
mcp dev main.py
```

This exposes the following MCP tools:

- `copy_to_clipboard(data: str)`: Copies text to the clipboard
- `paste_from_clipboard()`: Returns text from the clipboard
- `paste_image_from_clipboard()`: Returns images from the clipboard as base64-encoded PNG

## Development

This project uses modern Python tooling:

- [uv](https://github.com/astral-sh/uv) for dependency management

## License

MIT
sbcli-storage-tiering 12.2.19
CLI for managing SimplyBlock cluster


# SBCLI (SimplyBlock CLI)

Simplyblock provides a feature-rich CLI (command line interface) to deploy SimplyBlock Cluster and to manage the SimplyBlock Control plane

## Install

The CLI can be installed using pypi package [sbctl](https://pypi.org/project/sbctl/)

```
pip install --upgrade sbctl
```

# Components

## Simply Block Core
Contains core logic and controllers for the simplyblock cluster

## Simply Block CLI
The list of all the available CLI options can be here [CLI docs](./simplyblock_cli/README.md)

## SimplyBlock Web API

Web app that provides API to manage the cluster. More about this in [README.md](./simplyblock_web/README.md)


### local development

FoundationDB requires a client library (libfdb_c.dylib) for the Python bindings to interact with the database.
Depending on the OS architecture, please install the appropriate version from the official github repo

```
wget https://github.com/apple/foundationdb/releases/download/7.3.3/FoundationDB-7.3.3_arm64.pkg
```
setup the code on a management node and the webApp code can be developed by building the `docker-compose-dev.yml` file.

```
sudo docker compose -f docker-compose-dev.yml up --build -d
```