semvec/pypi-packages huggingface dataset:
data-merge 0.1.2
Python package for merging Excel and CSV files

# data_merge

`data_merge` is a Python package designed for effortlessly merging multiple Excel (`.xlsx`) or CSV files into a single consolidated file. Whether you need to combine financial reports, datasets, or logs, `data_merge` simplifies the process with minimal setup.

## Features
- Merge multiple Excel files in a folder into a single file.
- Merge multiple CSV files in a folder into a single file.
- Automatically handles indexing and preserves data integrity.

## Usage Example

```python
from data_merge.file_merger import FileMerger

# Define folder path and output path
folder_path = "path/to/your/files"
output_path = "path/to/save/merged_file.xlsx"

# Merge Excel files
merger = FileMerger(folder_path, output_path)
merger.merge_excel_files()

# Merge CSV files
merger.merge_csv_files()
```

## Installation
```pip install data_merge```

## Requirements
- Python 3.x
- Pandas

## Author
Developed by Ojo Ilesanmi. Reach out at ojoilesanmi89@gmail.com.
swarmbase-cli 0.0.2
A CLI for interacting with the swarmbase.ai API

+++

# SwarmBase.ai CLI

This CLI tool is for managing agents, frameworks, swarms, and tools with SwarmBase.ai. It uses `click` and provides commands for creating, listing, updating, and deleting various entities.

## Installation

To install the CLI, use pip:

<pre><div class="dark bg-gray-950 rounded-md border-[0.5px] border-token-border-medium"><div class="flex items-center relative text-token-text-secondary bg-token-main-surface-secondary px-4 py-2 text-xs font-sans justify-between rounded-t-md"><span>diff</span><div class="flex items-center"><span class="" data-state="closed"><button class="flex gap-1 items-center"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" fill="none" viewBox="0 0 24 24" class="icon-sm"><path fill="currentColor" fill-rule="evenodd" d="M7 5a3 3 0 0 1 3-3h9a3 3 0 0 1 3 3v9a3 3 0 0 1-3 3h-2v2a3 3 0 0 1-3 3H5a3 3 0 0 1-3-3v-9a3 3 0 0 1 3-3h2zm2 2h5a3 3 0 0 1 3 3v5h2a1 1 0 0 0 1-1V5a1 1 0 0 0-1-1h-9a1 1 0 0 0-1 1zM5 9a1 1 0 0 0-1 1v9a1 1 0 0 0 1 1h9a1 1 0 0 0 1-1v-9a1 1 0 0 0-1-1z" clip-rule="evenodd"></path></svg>Copy code</button></span></div></div><div class="overflow-y-auto p-4" dir="ltr"><code class="!whitespace-pre hljs language-diff">+++
pip install swarmbase
+++
</code></div></div></pre>

## Configuration

Before using the CLI, configure it with the base URL of the SwarmBase.ai API. This is done automatically the first time you run any command with the `--base-url` option. The configuration is saved in `~/.swarm_cli_config.json` for future use.

## Commands

### General Commands

* `--base-url`: Set the base URL of the SwarmBase.ai API.
* `--debug`: Enable debug logging.

### Agent Commands
openai-toolgen 0.3.1
A library for generating tools for OpenAI projects
Requires Python: >=3.6

A super simple tool to generate tool specification for the openai API.

## Install
`pip install openai-toolgen`

## Example
Example using Openai Completions:

```python
from typing import Annotated
from enum import Enum
from openai import OpenAI
from openai_toolgen import tool

class Unit(str, Enum):
    Celcius = "c"
    Farenheit = "f"

@tool("Call this function when the user wants to know the temperature")
def get_temperature(
        location: Annotated[str, "Location to fetch the tempereature from"],
        unit: Annotated[Unit, "Temperature will be returned in this unit"] = Unit.Celcius
    ):
    return { "temperature": 32, "unit": unit.value, "location": location }

client = OpenAI()
messages = [{"role": "user", "content": "What's the temperature in Stockholm today?"}]
completion = client.chat.completions.create(
    model="gpt-4o",
    messages=messages,
    tools=tool.export_all(),
    tool_choice="required"
)
```
Check out the tests for more details

## Features

### Enums
If the type of an argument is [enum.Enums](https://docs.python.org/3/library/enum.html#enum.Enum) it will be properly serialized according to [openai's spec](https://platform.openai.com/docs/api-reference/chat/create).
```python
>>> from openai_toolgen import tool
>>> from enum import Enum
>>> class Unit(str, enum):
...   celcius = "c"
...   farenheit = "f",
...
>>> @tool
...def get_temperature(unit: unit): pass
...
>>> tool.export_all()[0]['function']['parameters']['properties']
{
  'unit':
  {
    'type': 'string',
    'description': '',
    'enum': ['c', 'f']
  }
}
```

### Parameter descriptions
It is possible to use typing.Annotated to provide a description to the LLM:
```python
>>> from openai_toolgen import tool
>>> from typing import Annotated
>>> @tool
... def foo(bar:Annotated[str, "description of bar"]): pass
...
>>> tool.export_all()[0]['function']['parameters']['properties']
{
  'bar':
  {
    'type': 'string',
    'description': 'description of bar'
  }
}
```