semvec/pypi-packages huggingface dataset:
aikit-cli 0.1.0
A lightweight command-line tool for scaffolding minimal AI projects.
Requires Python: >=3.8

# aikit-cli

**aikit-cli** is a lightweight command-line tool for scaffolding minimal AI projects.  
It provides opinionated, ready-to-use boilerplate for common AI patterns.

---

## Installation

```bash
pip install aikit-cli
```

## Usage

Create a new project:

```bash
# Interactive mode
aikit-cli new my-bot

# One-liner
aikit-cli new my-bot --type chatbot --provider openai
```

### Options

| Option | Shorthand | Description | Default |
|--------|-----------|-------------|---------|
| `--type` | `-t` | Project type (`chatbot` or `rag`) | `chatbot` |
| `--provider` | `-p` | AI provider (`openai` or `ollama`) | `openai` |
| `--create-venv`| | Create a virtual environment | `False` |
| `--non-interactive` | | Fail if required options are missing instead of prompting | `False` |

### Examples

**Interactive Mode (Recommended)**:
```bash
aikit-cli new my-bot
```

**Quick Create (Chatbot with OpenAI)**:
```bash
aikit-cli new my-bot --type chatbot --provider openai
```

**Local RAG Project (with Ollama)**:
```bash
aikit-cli new local-rag --type rag --provider ollama
```

## Generated Structure

After creating a project, you'll get a clean structure similar to this:

```
my-bot/
├── .env                # Environment variables (API keys, etc.)
├── app/
│   ├── __init__.py
│   ├── main.py         # Entry point
│   ├── config.py       # Configuration settings
│   └── provider.py     # LLM provider wrapper
├── pyproject.toml      # Project dependencies
└── README.md
```

##  Running Your Project

1. Navigate to the created directory:
   ```bash
   cd my-bot
   ```
# TODO: Add poetry/uv support + dependencies
2. Install dependencies:
   ```bash
   pip install .  # or use poetry/uv
   ```

3. Configure environment:
   - For OpenAI: Add `OPENAI_API_KEY=sk-...` to `.env`.
   - For Ollama: Ensure Ollama is running (`ollama serve`).

4. Run the app:
   ```bash
   python app/main.py
   ```

## Contributing

Contributions are welcome! Please open an issue or submit a pull request.

## License

MIT
pydantic-ghostfolio 0.1.1
Pydantic models for Ghostfolio export/import data
Requires Python: >=3.10

# Pydantic Ghostfolio

Pydantic models for [Ghostfolio](https://github.com/ghostfolio/ghostfolio) export/import format.
This package allows you to parse, validate, and type-check Ghostfolio data in Python.

## Installation

```bash
pip install pydantic-ghostfolio
```

## Usage

See [examples/basic_usage.py](examples/basic_usage.py) for a complete example.

```python
from pydantic_ghostfolio import GhostfolioExport
import json

with open("ghostfolio-export.json", "r") as f:
    data = json.load(f)

export = GhostfolioExport(**data)
print(f"Export version: {export.meta.version}")
```

## References

The models are based on the Ghostfolio source code interfaces:

- **Export Response Schema**: [export-response.interface.ts](https://github.com/ghostfolio/ghostfolio/blob/main/libs/common/src/lib/interfaces/responses/export-response.interface.ts)
- **Activity Interface**: [activities.interface.ts](https://github.com/ghostfolio/ghostfolio/blob/main/libs/common/src/lib/interfaces/activities.interface.ts)
- **Prisma Schema**: [schema.prisma](https://github.com/ghostfolio/ghostfolio/blob/main/prisma/schema.prisma)

## Development

Run tests:
```bash
uv run pytest
```
rusgramm 0.1.1
Русскоязычный фреймворк для создания Telegram ботов
Requires Python: >=3.7

# Русграмм - Русскоязычный фреймворк для Telegram ботов

Русграмм - это фреймворк, который позволяет создавать Telegram ботов на русском языке с использованием интуитивно понятного синтаксиса.

## Установка

```bash
pip install rusgramm
```

## Быстрый старт

Создайте файл `главный.рус`:

```python
из m импорт Русграмм, Команда, Текст

бот = Русграмм("YOUR_BOT_TOKEN")

@бот.сообщение(Команда("start"))
фун старт(сообщение):
    сообщение.ответ("Привет! Я бот на Русграмме 😄")

@бот.сообщение(Текст("привет"))
фун приветствие(сообщение):
    сообщение.ответ("Привет 👋")

если __имя__ == "__главный__":
    бот.запуск()
```

Запустите бота:

```bash
rusgramm
```

## Основные конструкции

### Импорты
```python
из m импорт Русграмм, Команда, Текст
```

### Функции
```python
фун название_функции(параметры):
    # код функции
```

### Условия
```python
если условие:
    # код
иначе:
    # код
```

### Циклы
```python
для элемент в список:
    # код

пока условие:
    # код
```

## Обработчики сообщений

### Команды
```python
@бот.сообщение(Команда("start"))
фун обработчик(сообщение):
    сообщение.ответ("Ответ на /start")
```

### Текстовые сообщения
```python
@бот.сообщение(Текст("привет"))
фун обработчик(сообщение):
    сообщение.ответ("И тебе привет!")
```

### Все сообщения
```python
@бот.сообщение()
фун обработчик(сообщение):
    сообщение.ответ("Получено сообщение")
```

## Запуск

### Автоматический поиск файла
```bash
rusgramm
```
Ищет файлы в порядке: `бот главный.рус` → `главный.рус` → любой `.рус` файл

### Указание файла
```bash
rusgramm мой_бот.рус
```

### Через Python
```bash
python -m runner мой_бот.рус
```

## Переменные окружения

Установите токен бота через переменную окружения:

```bash
export BOT_TOKEN="your_token_here"
```

Тогда в коде можно не указывать токен:
```python
бот = Русграмм()  # возьмет из BOT_TOKEN
```

## Пример бота

```python
из m импорт Русграмм, Команда, Текст

бот = Русграмм()

@бот.сообщение(Команда("start"))
фун старт(сообщение):
    сообщение.ответ("👋 Привет! Я бот на Русграмме")

@бот.сообщение(Команда("help"))
фун помощь(сообщение):
    сообщение.ответ("📋 Справка:\n/start - запуск\n/help - помощь")

@бот.сообщение(Текст("как дела?"))
фун как_дела(сообщение):
    сообщение.ответ("😊 Отлично! А у тебя?")

если __имя__ == "__главный__":
    бот.запуск()
```

## Лицензия

MIT License
echandia-analytics-tool 1.0.0
Random stuff

# Battery Model CLI

This package provides a command-line interface (CLI) for ECHANDIA Analytics tools.

## Installation from GitHub Packages

### 1. Generate a GitHub Personal Access Token (PAT)
- Go to your GitHub account settings → Developer settings → Personal access tokens.
- Generate a token with the `read:packages` scope.

### 2. Configure pip to use GitHub Packages
Create a `.pypirc` file in your home directory with the following content:

```
[distutils]
index-servers =
    github

[github]
repository: https://pypi.pkg.github.com/OWNER
username: YOUR_GITHUB_USERNAME
password: YOUR_PERSONAL_ACCESS_TOKEN
```
Replace `OWNER` with your GitHub username or organization, and fill in your username and token.

### 3. Install the package
Run:
```
pip install --extra-index-url https://pypi.pkg.github.com/OWNER battery-model
```

## Usage
After installation, you can use the CLI by running:
```
eat
```

## Access
Only users with access to the GitHub repository and a valid PAT can install this package.

---
For more information, see the repository or contact the maintainer.
sas7bdat-overview 0.1.0
Summarize SAS7BDAT register coverage and variable availability.
Requires Python: >=3.9

# sas7bdat-overview

Summarize SAS7BDAT coverage by register, period, and variable availability.

## Install (wheel)

Build a wheel locally and upload to your PyPI mirror:

```
python -m pip install maturin
maturin build --release
```

The wheel will be under `target/wheels/`.

## Usage

Basic metadata-only scan (fast):

```
sas7bdat-overview /path/to/sas/files --out-dir /path/to/output
```

Include per-variable value profiles (slower, scans all rows):

```
sas7bdat-overview /path/to/sas/files --out-dir /path/to/output --profile
```

Include unique person/family counts (slower, scans all rows):

```
sas7bdat-overview /path/to/sas/files --out-dir /path/to/output --compute-ids
```

Restrict to specific registers (case-insensitive):

```
sas7bdat-overview /path/to/sas/files --registers lpr_diag,ind
```

## Outputs

When `--out-dir` is set, the tool writes:

- `register_inventory.csv` — register coverage (first/last year, file count, column count)
- `variable_coverage.csv` — variable coverage by register and year
- `variable_profile.csv` — per-variable missingness and ranges (only populated if `--profile` is used)
- `inventory_summary.md` — human-readable summary table

The JSON output (`--output`) includes the full raw summaries.

## File naming

Handles filenames like:

- `<register>.sas7bdat`
- `<register><year>.sas7bdat`
- `<register><year><month>.sas7bdat`
- `<register>_YYYY_MM.sas7bdat`
- `<register>-YYYY-MM.sas7bdat`

Register names may include underscores.
quantities 0.16.4
Support for physical quantities with units, based on numpy
Requires Python: >=3.10
Keywords: quantities, units, physical, constants

==========
quantities
==========

Quantities is designed to handle arithmetic and
conversions of physical quantities, which have a magnitude, dimensionality
specified by various units, and possibly an uncertainty. See the tutorial_
for examples. Quantities builds on the popular numpy library and is
designed to work with numpy ufuncs, many of which are already
supported. Quantities is actively developed, and while the current features
and API are stable, test coverage is incomplete so the package is not
suggested for mission-critical applications.

|pypi version|_ |Build status|_

.. |pypi version| image:: https://img.shields.io/pypi/v/quantities.png
.. _`pypi version`: https://pypi.python.org/pypi/quantities
.. |Build status| image:: https://github.com/python-quantities/python-quantities/actions/workflows/test.yml/badge.svg?branch=master
.. _`Build status`: https://github.com/python-quantities/python-quantities/actions/workflows/test.yml
.. _tutorial: http://python-quantities.readthedocs.io/en/latest/user/tutorial.html


A Python package for handling physical quantities. The source code and issue
tracker are hosted on GitHub:

https://www.github.com/python-quantities/python-quantities

Download
--------
Get the latest version of quantities from
https://pypi.python.org/pypi/quantities/

To get the Git version do::

    $ git clone git://github.com/python-quantities/python-quantities.git


Documentation and usage
-----------------------
You can find the official documentation at:

http://python-quantities.readthedocs.io/

Here is a simple example:

.. code:: python

   >>> import quantities as pq
   >>> distance = 42*pq.metre
   >>> time = 17*pq.second
   >>> velocity = distance / time
   >>> "%.3f %s" % (velocity.magnitude, velocity.dimensionality)
   '2.471 m/s'
   >>> velocity + 3
   Traceback (most recent call last):
     ...
   ValueError: Unable to convert between units of "dimensionless" and "m/s"

Installation
------------

To install quantities itself, simply run::

    $ pip install quantities


Tests
-----
To execute all tests, install pytest::

    $ python -m pip install pytest

And run::

    $ pytest

in the current directory. The master branch is automatically tested by
GitHub Actions.

Author
------
quantities was originally written by Darren Dale, and has received contributions from `many people`_.

.. _`many people`: https://github.com/python-quantities/python-quantities/graphs/contributors

License
-------
Quantities only uses BSD compatible code.  See the Open Source
Initiative `licenses page <http://www.opensource.org/licenses>`_
for details on individual licenses.

See `doc/user/license.rst <doc/user/license.rst>`_ for further details on the license of quantities