semvec/pypi-packages huggingface dataset:
askora 0.0.2
A unified CLI for AI providers like OpenAI and Ollama
License: MIT
Requires Python: >=3.9

# AskOra

AskOra is a unified Python CLI for interacting with multiple AI providers like OpenAI, Ollama, DeepSeek and Anthropic(Claude). Send prompts, get responses, and switch between providers seamlessly, all from the command line.

---

## Features

* Single CLI to interact with multiple AI providers
* Supports **OpenAI**, **Ollama**, **Anthropic(Claude)**, **DeepSeek** and more in the future
* Returns structured responses with tokens used and execution time
* Supports **sync** and **async** execution
* Clean error handling for missing models, invalid API keys, etc.
* Available on **PyPI** as `askora`

---

## Installation

Clone the repo and install dependencies:

```bash
git clone https://github.com/jetroni/askora.git
cd askora
python -m venv .venv
source .venv/bin/activate   # On Windows: .venv\Scripts\activate
pip install -r requirements.txt
```

Or install directly from PyPI:

```bash
pip install askora
```

(Optional) Make the CLI globally executable:

```bash
pip install --editable .
```

---

## Usage

Basic usage:

```bash
askora --type openai --prompt "Hello AI"
```

Run with async mode:

```bash
askora --type openai --prompt "Hello AI" --async-mode
```

Ollama example (with base URL):

```bash
askora --type ollama --base-url http://localhost:11434 --model codellama --prompt "Hello"
```

---

## CLI Options

| Option         | Description                                       |
| -------------- | ------------------------------------------------- |
| `--type`       | AI provider type (openai, ollama)                 |
| `--prompt`     | Text prompt to send to the AI                     |
| `--key`        | API key for providers that require authentication |
| `--model`      | Model name to use (defaults vary per provider)    |
| `--base-url`   | Base URL for self-hosted providers like Ollama    |
| `--async-mode` | Run asynchronously (flag, no value needed)        |

---

## Response Structure

All responses are returned as a structured JSON object:

```json
{
  "provider": "openai",
  "model": "gpt-4o-mini",
  "output": "Hello! How can I assist you today?",
  "raw": {...},
  "tokens_used": 17,
  "duration_ms": 543
}
```

---

## Contributing

We welcome contributions!

* Add support for new AI providers
* Improve error handling
* Enhance async execution and CLI experience

Please fork the repo and submit a pull request.

---

## License

MIT License. Free to use and modify.

---

## PyPI

AskOra is published on PyPI. Install via:

```bash
pip install askora
```

Stay up to date with the latest releases and check the package page: [https://pypi.org/project/askora/](https://pypi.org/project/askora/)
steamio 1.1.3
A Python wrapper for the Steam API
License: MIT
Requires Python: <4.0,>=3.11
Keywords: steam.py, steam, steamio, steam-api

# steam.py

A modern, easy to use, and async ready package to interact with the Steam API. Heavily inspired by
[discord.py](https://github.com/Rapptz/discord.py).

![Supports](https://img.shields.io/pypi/pyversions/steamio)
![Version](https://img.shields.io/pypi/v/steamio?color=%2366c0f4)
![License](https://img.shields.io/github/license/Gobot1234/steam.py)
[![GitHub issues](https://img.shields.io/github/issues-raw/Gobot1234/steam.py)](https://github.com/Gobot1234/steam.py/issues)
[![GitHub stars](https://img.shields.io/github/stars/Gobot1234/steam.py)](https://github.com/Gobot1234/steam.py/stargazers)
[![Discord](https://img.shields.io/discord/678629505094647819?color=7289da&label=Discord&logo=discord)](https://discord.gg/MQ68WUS)
[![Documentation Status](https://github.com/Gobot1234/steam.py/actions/workflows/docs.yml/badge.svg)](https://github.com/Gobot1234/steam.py/actions/workflows/docs.yml)

## Key Features

- Modern Pythonic API using `async`/`await` syntax
- Command extension to aid with bot creation
- Easy to use with an object-oriented design
- Fully typed hinted for faster development

## Installation

**Python 3.10 or higher is required**

To install the library just run either of the following commands:

```sh
# Linux/macOS
python3 -m pip install -U steamio
# Windows
py -m pip install -U steamio
```

Or for the development version.

```sh
# Linux/macOS
python3 -m pip install -U "steamio @ git+https://github.com/Gobot1234/steam.py@main"
# Windows
py -m pip install -U "steamio @ git+https://github.com/Gobot1234/steam.py@main"
```

## Quick Example

```python
import steam


class MyClient(steam.Client):
    async def on_ready(self) -> None:
        print("Logged in as", self.user)

    async def on_trade(self, trade: steam.TradeOffer) -> None:
        if not trade.is_our_offer():
            await trade.user.send("Thank you for your trade")
            print(f"Received trade: #{trade.id}")
            print("Trade partner is:", trade.user)
            print("We would send:", len(trade.sending), "items")
            print("We would receive:", len(trade.receiving), "items")

            if trade.is_gift():
                print("Accepting the trade as it is a gift")
                await trade.accept()


client = MyClient()
client.run("username", "password")
```

## Bot Example

```python
from steam.ext import commands

bot = commands.Bot(command_prefix="!")


@bot.command
async def ping(ctx: commands.Context) -> None:
    await ctx.send("Pong!")


bot.run("username", "password")
```

## Links

- [Documentation](https://steam-py.github.io/docs/latest)
- [Official Discord Server](https://discord.gg/MQ68WUS)
labdatautils 0.1.2
Experimental data utilities: error propagation and LaTeX table generator
License: MIT
Requires Python: >=3.8

# labdatautils

A Python library for **experimental data analysis and reporting**.  
Includes tools for **error propagation** and **LaTeX-ready table formatting** — all with consistent significant-figure handling.

## Features

- **Error propagation** via finite difference derivatives, with correct significant figures.
- **LaTeX table generation** with support for merged value ± error columns.
- Designed for **clarity** and **reproducibility** in lab reports.

## Installation

```bash
pip install labdatautils
```
---

## Function Reference

### 1. `propagate(func, *args)`

**Arguments:**
- `func` *(callable)* — Function whose result and uncertainty are to be calculated.
- `*args` — Values and uncertainties, alternating: `val1, err1, val2, err2, ...`  
  Each can be a float, list, or NumPy array (all arrays must have the same length).

**Returns:**
- `values` *(ndarray)* — Computed function results.
- `errors` *(ndarray)* — Propagated uncertainties.

---

### 2. `generate_latex_table(column_headers, data_columns, **kwargs)`

**Arguments:**
- `column_headers` *(list of str)* — Ordered list of column names to display.
- `data_columns` *(sequence of arrays)* — One array per column, in the same order as `column_headers`.  
  Each array should contain the values for that column.
- `caption` *(str, optional)* — Table caption. Default: `"Data Table"`.
- `label` *(str, optional)* — LaTeX label for referencing. Default: `"tab:data"`.
- `error_map` *(dict or list of str, optional)* — Maps error columns to their associated value column.  
  Example: `{"dx": "x", "dy": "y"}` or `["dx:x", "dy:y"]`.
- `merge_error_style` *(str, optional)* — How to display value and error pairs:  
  `"separate"` (two columns), `"pm"` (e.g. `1.23 ± 0.04`), `"paren"` (e.g. `1.23(4)`). Default: `"separate"