semvec/pypi-packages huggingface dataset:
ryoma-ai 0.1.5
AI Powered Data Platform
Requires Python: >=3.9
Keywords: Artificial Intelligence, Code Generation, Data Analysis

# Ryoma

Ryoma lib is the core component of the project which includes:
- **Data Sources** that can be used to fetch data from different sources
- **Agents** that can be used to process data with AI models
- **Tools** that can be used by agent to process data

## Installation

### Basic Installation
```bash
pip install ryoma_ai
```

### Installing with Optional Dependencies

Ryoma AI uses lazy imports for datasource dependencies, so you only need to install the dependencies for the datasources you plan to use:

```bash
# For PostgreSQL support
pip install ryoma_ai[postgres]

# For MySQL support  
pip install ryoma_ai[mysql]

# For Snowflake support
pip install ryoma_ai[snowflake]

# For BigQuery support
pip install ryoma_ai[bigquery]

# For DuckDB support
pip install ryoma_ai[duckdb]

# For DynamoDB support
pip install ryoma_ai[dynamodb]

# For Apache Iceberg support
pip install ryoma_ai[iceberg]

# For PySpark support
pip install ryoma_ai[pyspark]

# Multiple datasources
pip install ryoma_ai[postgres,mysql,duckdb]
```

## Usage

```python
from ryoma_ai.datasource.postgres import PostgresDataSource
from ryoma_ai.agent.sql import SqlAgent

datasource = PostgresDataSource("postgresql://user:password@localhost/db")
sql_agent = SqlAgent("gpt-3.5-turbo").add_datasource(datasource)
sql_agent.stream("Get the top 10 rows from the data source")
```

## Documentation
Visit the [documentation](https://project-ryoma.github.io/ryoma/) for more information.
python-venusclient 2.5.0
Python client for venus API
Requires Python: >=3.8

========================
Team and repository tags
========================

.. image:: https://governance.openstack.org/tc/badges/python-venusclient.svg
    :target: https://governance.openstack.org/tc/reference/tags/index.html

.. Change things from this point on

==================
python-venusclient
==================

.. image:: https://img.shields.io/pypi/v/python-venusclient.svg
    :target: https://pypi.python.org/pypi/python-venusclient/
    :alt: Latest Version

python-venusclient is a python bindings to the OpenStack Venus API. There's
a Python API (the ``venusclient`` module), and a command-line script
(``venus``). Each implements 100% of the OpenStack Venus API.
nltkaz 0.2.0
A natural language processing toolkit designed for the Azerbaijani language.
Requires Python: >=3.6

![NLTKaz Banner](https://i.imgur.com/JecGkI0.png)

# NLTKAZ 📚

**NLTKAZ** is a natural language processing toolkit designed for the Azerbaijani language making it easier to preprocess Azerbaijani text for NLP tasks.

## Installation ⬇️
```bash
pip install nltkaz
```

## Features 🧩
Currently provided features:
- **Stemming**: Reduce words to their root forms.
- **Stopword Removal**: Easily remove common Azerbaijani stopwords from text.
- **Tokenization**: Tokenize text into words, sentences, or tweets.

## Usage ⚙️
### Stemming
```python
from nltkaz import Stemmer

# Initialize stemmer with the appropriate keyboard type
# Use 'az' for Azerbaijani text or 'en' if the text is typed using an English keyboard
stemmer = Stemmer(keyboard="az")

# Stem your string
stemmed_string = stemmer.stem("your_string")
```

### Stopword Removal
```python
from nltkaz import load, remove

# Load stopwords
stopwords = load()

# Remove stopwords from the given string
result = remove(stopwords=stopwords, sentence="your_string")
```

### Tokenization

#### Word Tokenizer
```python
from nltkaz import wordTokenize

words = wordTokenize("your_string")
```

#### Sentence Tokenizer
```python
from nltkaz import sentenceTokenize

sentences = sentenceTokenize("your_string")
```

#### Tweet Tokenizer
```python
from nltkaz import tweetTokenize

tweets = tweetTokenize("your_string")
```

## Author 🧑‍💻
- **Nagi Nagiyev**  

## Contact 📧
Gmail: nagiyevnagi01@gmail.com.

Linkedin: https://www.linkedin.com/in/naginagiyev/

## License 📜
MIT License

---

> This project is in early development. Contributions and feedback are welcome! 🤝
otto-api42 0.1.5
The 42 Intranet API as a powerful and Py-ful package
Requires Python: >=3.10

# otto_api42

**This is a fork from [HiveHelsinki's api42](https://github.com/hivehelsinki/42api-lib).**  
The aim of this fork is to facilitate API communication for student by Pythonizing the results from the API.
tips-cli-tool 0.1.2
A simple CLI tool for creating temporary notes that are automatically deleted after editing.
Requires Python: >=3.6

# Tips CLI Tool

A simple command-line tool for creating temporary notes that are automatically deleted after editing.

## Features

*   **Quick Note Creation**: Instantly create a temporary note file with a timestamped name.
*   **Configurable Editor**: Use your preferred editor (VS Code, Notepad, Notepad++, etc.).
*   **Automatic Cleanup**: The temporary file is automatically deleted when you close the editor.
*   **Cross-Platform**: Works on Windows, macOS, and Linux.

## Installation

```bash
pip install tips-cli-tool
```

## Usage

Simply run the command:

```bash
tips
```

This will create a new temporary `.md` file and open it in your default editor (VS Code by default).

### Options

*   `-e EDITOR`, `--editor EDITOR`: Specify the editor to use (overrides config).
*   `-x EXTENSION`, `--extension EXTENSION`: Specify the file extension (overrides config).
*   `-c CONFIG`, `--config CONFIG`: Path to the configuration file.

### Examples

```bash
# Use Notepad on Windows
tips --editor notepad

# Create a temporary .txt file
tips --extension .txt

# Use a custom configuration file
tips --config /path/to/my/config.yaml
```

## Configuration

Tips CLI Tool uses a configuration file to define default settings and editor commands.

The configuration file is located at:

*   **Linux/macOS**: `~/.config/tips/config.yaml` or `~/.tips_config.yaml`
*   **Windows**: `~/.tips_config.yaml` (or potentially `%APPDATA%/Tips/config.yaml`)

### Example Configuration (`config.yaml`)

```yaml
# Default editor to use
default_editor: "vscode"

# Default file extension
default_extension: ".md"

# Editor configurations
editors:
  vscode:
    command: "code"
    args: ["--wait"]

  notepad:
    command: "notepad"
    args: []

  notepadpp:
    command: "notepad++"
    args: ["-multiInst", "-nosession"]

  sublime:
    command: "subl"
    args: ["--wait"]

  vim:
    command: "vim"
    args: []

  gvim:
    command: "gvim"
    args: ["--nofork"]
```

## How It Works

1.  When you run `tips`, it creates a new file in `~/tips-temp/` with a name like `YYYYMMDD_HHMMSS_microseconds.md`.
2.  It then launches your configured editor to open this file.
3.  The tool waits for the editor process to finish (typically when you close the editor window).
4.  Once the editor is closed, the temporary file is automatically deleted.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
speedy-bg 1.0.0
Speedy Express Service
Requires Python: >=3.6

# speedy

📦 A simple Python wrapper for the Speedy.bg REST API

```python
# Example usage of SpeedyAPI
from speedy_bg.api import SpeedyAPI


if __name__ == "__main__":
    api = SpeedyAPI("your_username", "your_password")

    # 1) Find a country
    country = api.find_country(name="BULGARIA")
    print("Country:", country)

    # 2) Get contract clients (useful to know your clientId)
    clients = api.get_contract_clients()
    print("Clients:", clients)

    # 3) Find site by post code
    site = api.find_site(country_id=100, post_code="1000")  # 100 = Bulgaria ID
    print("Site by postcode:", site)

    # 4) Find office in Sofia
    office = api.find_office(name="SOFIA")
    print("Offices:", office)

    # 5) Create shipment
    sender = {
        "clientId": 123456,  # from get_contract_clients
        "contactName": "Sender Name",
        "phone1": "0888123456"
    }
    recipient = {
        "privatePerson": True,
        "contactName": "John Doe",
        "phone1": "0899123456",
        "addressLocation": {
            "countryId": 100,
            "siteId": 68134  # e.g. Sofia
        }
    }
    service = {"serviceId": 505}   # example: delivery service ID
    content = {"parcelsCount": 1, "totalWeight": 2.5}
    payment = {"courierServicePayer": "SENDER"}

    shipment = api.create_shipment(sender, recipient, service, content, payment)
    print("Created shipment:", shipment)

    # 6) Print waybill as PDF
    if "parcels" in shipment:
        parcel_ids = [p["id"] for p in shipment["parcels"]]
        pdf_data = api.print_waybill(parcel_ids)
        with open("waybill.pdf", "wb") as f:
            f.write(pdf_data)
        print("Waybill saved as waybill.pdf")

    # 7) Calculate price for a destination
    calc = api.calculate(sender={"clientId": 123456},
                         recipient={"privatePerson": True, "addressLocation": {"countryId": 100, "siteId": 68134}})
    print("Calculation:", calc)
```
econt-bg 1.0.5
Econt Express Service
Requires Python: >=3.6

# econt
A library for use econt.com delivery service

#### Install
```bash
pip install econt_bg
```

#### Example

```python
from econt_bg.api import Econt
econt = Econt()
econt.get_countries()
econt.get_cities()
econt.get_offices()
econt.get_streets()
econt.get_streets_by_city(city_post_code="1407")
econt.get_offices_by_city(city_post_code="1407")
econt.get_quarters()
econt.get_seller_addresses()
econt.get_regions()
econt.get_clients()
```
mcp-fofa 0.1.0
Add your description here
Requires Python: >=3.11.13

## FOFA MCP
基于 Model Context Protocol (MCP) 的fofa数据查询。


## 工具列表
| name | description |
| ----------- | ----------- |
| auth  | fofa搜索之前所必须的key验证 |
| search | ofa搜索 |

## MCP 服务器配置
```
{
  "mcpServers": {
    "mcp-fofa": {
      "isActive": true,
      "name": "calculator",
      "type": "stdio",
      "command": "uv",
      "args": [
        "--directory",
        "/Users/xiezi/explore/mcp-fofa/src",  # 替换为自己的路径
        "run",
        "-m",
        "mcp_fofa"
      ]
      }
  }
}
```