semvec/pypi-packages huggingface dataset:
rpa-sap 1.2.7
SAPGUI scripting automation
Requires Python: >=3.10

# RPA_SAP
Python module delivers some actions to automate SAPGUI operations (Sap Scripting). The module is compatible with Robocorp.

## Installation
To install the package, run:

```sh
pip install rpa-sap
```

## Example
### Open new SAPGUI session
```python
from rpa_sap import SapGui

sapgui = SapGui()

sapgui.open_new_session(connection_string, user_id, password, client, language)
```

## Features
- Open and close SAP sessions
- Run SAP transactions
- Interact with SAP GUI elements (buttons, text fields, checkboxes, etc.)
- Handle SAP GridView and TableControl
- Export data to various formats (CSV, Excel)

## Dependencies
- pandas >= 1.4.4
- pywin32 >= 303
- wmi >= 1.5.1

## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Contributing
Contributions are welcome! Please read the [contributing guidelines](https://github.com/21010/rpa-sap/blob/main/CONTRIBUTING.md) for more details.

## Contact
For any questions or suggestions, feel free to open an issue on the [GitHub repository](https://github.com/21010/rpa-sap).
hdr-conversion 0.1.3
tools for converting HDR images between different formats
Requires Python: >=3.11

# HDR Format Conversion Tool

[简体中文](README-zhCN.md) | [English](README.md)

> **Important Note**: In alpha stage, API may change frequently. Currently, color conversion may be incorrect. This project is still in a very early stage, please submit issues or contact the author directly if you encounter any problems.

API Reference: [https://jackchou00.github.io/hdr-conversion](https://jackchou00.github.io/hdr-conversion/)

## Project Overview

This project provides Python-based research on HDR format parsing and writing, supporting parsing, writing, and conversion of multiple formats including UltraHDR, Adaptive Gainmap (ISO 21496-1), and pure PQ/HLG formats (ISO 22028-5).

Note: This project is for research and learning purposes only and does not aim for production readiness.

## Getting Started

To install, using `uv` (recommended):

```bash
uv add hdr-conversion
```

or use `pip`:

```bash
pip install hdr-conversion
```

The package can be imported as follows:

```python
import hdrconv
```

## Features

### Parsing

For UltraHDR and Adaptive Gainmap formats, supports structured extraction of:

- Main image data
- Gainmap image data
- Gainmap metadata

For pure PQ/HLG formats, supports extraction of image data and related metadata.

Add experimental support for iOS 26 HDR screenshot parsing.

### Writing

Writes image data and structured metadata into corresponding formats.

UltraHDR and Adaptive Gainmap formats are implemented through manual byte stream editing combined with existing library JPEG encoding capabilities, while pure PQ/HLG formats are implemented through existing libraries.

UltraHDR I/O APIs: `read_ultrahdr()` / `write_ultrahdr()`.

### Conversion

Calculates alternate images based on metadata to enable conversion between Gainmap and pure HDR formats.

## Reference Standards

- [UltraHDR](https://developer.android.com/media/platform/hdr-image-format): Version 1.1 released in April 2025
- [ISO 21496-1](https://www.iso.org/standard/86775.html)
- [ISO 22028-5](https://www.iso.org/standard/81863.html)

## License

MIT. Please refer to the respective LICENSE files for specific format and dependency details.
cratonml 0.1.1.38
Python application for W-Seis
Requires Python: <3.13,>=3.11

# CratonML

# Использование:


+ Установка зависимостей
```
$ pip install poetry 
$ poetry install
```
+ Сборка библиотеки
```
$ poetry build
```
# Логика версионирования CHANGELOG:

M.N.K.L

M - за глобальный релиз отвечает (выход в прод, закрытие этапа) 
N - при добавлении нового модуля, либо изменения старых, но без поддержки расчета прошлых версий
K - при добавлении новых функциональностей в существующих модулях (функции, класс и тд)
L - при изменении текущего функционала

При изменении номера, все что правее по индексу меняется на ноль.
Подразумевается что тесты не входят в пулл changelog, но если отдельно заливаются то менять L
Новые записи вносить вверх файла CHANGELOG
mbnpy 0.1.14
MBNpy is a Python package for Bayesian network applications for large-scale system events (i.e. high-dimensional data).
Requires Python: >=3.8

# MBNpy

## Overview
**MBNpy** is a Python toolkit for **matrix-based Bayesian network (MBN)**--an alternative data structure to conventional BN. MBN is designed to handle **problems with a large number of parent nodes**, where conventional BN tools often fall short. 
Example applications include [transport networks](https://doi.org/10.1016/j.ress.2019.01.007) and [pipeline networks](https://doi.org/10.1016/j.ress.2021.107468).

## Contact
If you have discussion points, refer to the [discussions tab](https://github.com/jieunbyun/MBNpy/discussions).  
If you have need support, refer to the [issues tab](https://github.com/jieunbyun/MBNpy/issues).

## Installation
### Install using pip
MBNpy requires **Python 3.12+**. To install using pip, run:
```bash
pip install mbnpy
```
### Downloading files from GitHub (development version)
```bash
git clone git@github.com:jieunbyun/MBNpy.git
cd MBNpy
```

## Documentation
For documentation, refer to the [MBNpy docs](https://jieunbyun.github.io/MBNpy-docs/).
For research news and blog articles, refer to the [MBNpy blog](https://jieunbyun.github.io/MBNpy/).

## License
MBNpy is distributed under the MIT License

Copyright (c) <2025> <Ji-Eun Byun>

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

## Referencing MBNPy
If you use this software for publication, please cite:

Byun, J. E. & Song, J. (2021). Generalized matrix-based Bayesian network for multi-state systems. *Reliability Engineering & System Safety,* 211, 107468.
WeeknoteBot 1.10.0
A bot for generate WeekNote for Hugo
Requires Python: >=3.10

# WeekNote Bot

This is a little script for generate a WeekNote for your Hugo static site.

## Run it

You launch after installing with

``` bash
weeknote
```

if you have your config at **~/.config/weeknote_bot/config.json** or you can run the command with the path of the config

``` bash
weeknote -config <path-of-the-config>
```

If it is the first time you run it, it will generate a black config and end the execution of the program
redis-fs 0.1.0
A unified file-system-like storage API with Redis and local filesystem backends
Requires Python: >=3.11
Keywords: redis, filesystem, storage, async

# redis-fs

A unified file-system-like storage API with Redis and local filesystem backends.

## Features

- **Unified API**: Same interface regardless of backend
- **Async-first**: Built on `asyncio`
- **Flexible backends**: Local FS, Redis, or both
- **Automatic sync**: Mirror Redis changes to local filesystem
- **Bulk operations**: Upload/download entire directory trees
- **Upstash support**: Works with Upstash Redis for serverless

## Installation

```bash
# With uv (recommended)
uv add redis-fs

# With pip
pip install redis-fs
```

## Quick Start

```python
import asyncio
from redis_fs import RedisFs

async def main():
    # Filesystem only
    async with RedisFs(fs_root="/tmp/data") as rfs:
        await rfs.write_text("hello.txt", "Hello, World!")
        content = await rfs.read_text("hello.txt")
        print(content)

    # Redis only
    async with RedisFs(redis="redis://localhost:6379", redis_prefix="myapp") as rfs:
        await rfs.write_text("config.json", '{"debug": true}')

    # Both with sync
    async with RedisFs(
        redis="redis://localhost:6379",
        redis_prefix="myapp",
        fs_root="/tmp/data"
    ) as rfs:
        await rfs.start_sync()
        await rfs.write_text("data.txt", "Synced!")
        await rfs.stop_sync()

asyncio.run(main())
```

## Documentation

See the [full documentation](https://yaakovb.github.io/redis-fs/) for:

- [Usage Guide](https://yaakovb.github.io/redis-fs/usage/)
- [Testing](https://yaakovb.github.io/redis-fs/testing/)
- [Build & Publish](https://yaakovb.github.io/redis-fs/publishing/)
- [API Reference](https://yaakovb.github.io/redis-fs/api/)

## License

MIT License - see [LICENSE](LICENSE) for details.
logscale 0.1.5
Compute orders of magnitude.
Requires Python: >=3.10

# logscale

[![Actions Status][actions-badge]][actions-link]
[![Documentation Status][rtd-badge]][rtd-link]

[![PyPI version][pypi-version]][pypi-link]
[![Conda-Forge][conda-badge]][conda-link]
[![PyPI platforms][pypi-platforms]][pypi-link]

[![GitHub Discussion][github-discussions-badge]][github-discussions-link]

[![Coverage][coverage-badge]][coverage-link]

This Python package provides a single function, `order_of_magnitude()`, which
computes and returns the order of magnitude of a given number in a standardized
string format.

The order of magnitude gives a compact representation of a number as a product
of a coefficient and a power of 10, where the coefficient is constrained to lie
within the interval [1/√10, √10). For more information, see the
[wikipedia article](https://en.wikipedia.org/wiki/Order_of_magnitude) on orders
of magnitude.

## Installation

If you are using `uv`, you can install the package from PyPI with:

    uv pip install logscale

Alternatively, with regular `pip`:

    pip install logscale

## Examples

```python
from logscale import order_of_magnitude

order_of_magnitude(129)  # "1.3e2"
order_of_magnitude(0.0001)  # "1.0e-4"
order_of_magnitude(456)  # "0.46e3"
order_of_magnitude(70.2)  # "0.70e2"
order_of_magnitude(0)  # "0.0e0"
```

<!-- prettier-ignore-start -->
[actions-badge]:            https://github.com/8-hat/logscale/workflows/CI/badge.svg
[actions-link]:             https://github.com/8-hat/logscale/actions
[conda-badge]:              https://img.shields.io/conda/vn/conda-forge/logscale
[conda-link]:               https://github.com/conda-forge/logscale-feedstock
[github-discussions-badge]: https://img.shields.io/static/v1?label=Discussions&message=Ask&color=blue&logo=github
[github-discussions-link]:  https://github.com/8-hat/logscale/discussions
[pypi-link]:                https://pypi.org/project/logscale/
[pypi-platforms]:           https://img.shields.io/pypi/pyversions/logscale
[pypi-version]:             https://img.shields.io/pypi/v/logscale
[rtd-badge]:                https://readthedocs.org/projects/logscale/badge/?version=latest
[rtd-link]:                 https://logscale.readthedocs.io/en/latest/?badge=latest
[coverage-badge]:           https://codecov.io/github/8-hat/logscale/branch/main/graph/badge.svg
[coverage-link]:            https://codecov.io/github/8-hat/logscale

<!-- prettier-ignore-end -->
edmkit 0.0.1a1
Simple EDM (Empirical Dynamic Modeling) library
Requires Python: >=3.13

# edmkit

This library is a collection of tools and utilities that are useful for Empirical Data Modeling (EDM) and related tasks. The library is designed to be fast and lightweight, and easy to use.

::: warning
This library is still under intensive development so API may change in the future.
:::

## Installation

To install the library, you can use pip:

```bash
pip install edmkit
```

Or you can also use [uv](https://docs.astral.sh/uv/):

```bash
uv add edmkit
```

## Usage

Most of the functions accept and return `numpy` arrays or `edmkit.Tensor`(alias to `tinygrad.Tensor`).
easygems 0.1.4
Processing tools around km-scale earth system modeling
Requires Python: >=3.10

# easygems python package

## install

The latest released version can be installed using:

```
pip install easygems
```

## developing

This project uses [ruff](https://github.com/astral-sh/ruff) for code formatting and [pre-commit](https://pre-commit.com/) to run the formatter automatically.

Please ensure that you have `pre-commit` configured locally by running:

```
pre-commit install
```
iflow-mcp_kutsushitaneko_mcp-server-for-oracle-database 0.1.0
MCP Server for Oracle Database - Oracle Database用のMCPサーバー
Requires Python: >=3.11

# MCP Server for Oracle Database（極めて実験的）

Oracle Database用のMCP（Model Context Protocol）サーバーの実験的な実装です。このサーバーは、AIアプリケーションがOracle Databaseに対してSQLクエリを実行し、その結果を取得するためのものです。MCPサーバーはローカルで実行されます。Cursor や Cline などの MCP クライアントから呼び出してシームレスなデータベース体験を提供することを目指してます。

## 機能

- Oracle DatabaseへのSQLクエリ実行
- テーブル構造の取得
- セキュリティ対策（クエリ長制限、危険なキーワードチェック）
    - 最小限のセキュリティ対策のみ施されています。外部からアクセスできないローカルな環境でのみ使用してください。
- 結果のフォーマット機能（LLMに呼んでもらうものなので、余計なことをしているかも）

## 必要条件

- Python 3.11以上
- Oracle  Databaseへのアクセス権限
- 必要な環境変数の設定（.envファイル）
- uv（高速なPythonパッケージマネージャー）

※テストは、Windows 11 のみで行っています。Linux/Mac の場合は、ディレクトリパスの表記などは適宜読み替えてください。

## セットアップ

1. リポジトリをクローン:
```bash
git clone [repository-url]
cd mcp-server-for-oracle-database
```

2. 仮想環境を作成して有効化:
```bash
uv venv .venv
```
```bash:Python仮想環境の有効化（Linux/Mac/Windows の gitbash など）
source .venv/bin/activate
```
```PowerShell:Python仮想環境の有効化（Windows PowerShell）
.venv\Scripts\activate
```

3. 依存パッケージをインストール:
```bash
uv pip install -r requirements.txt
```

4. 環境変数の設定:
`.env`ファイルを作成し、以下の情報を設定:
```
ORACLE_USER=your_username
ORACLE_PASSWORD=your_password
ORACLE_DSN=your_dsn
```

## 提供されるツール

### execute_oracle
SQLクエリ（SELECT文のみ）を実行し、結果をフォーマットして返します。
- パラメータ:
  - query: SQLクエリ（SELECT文のみ）
  - params: バインド変数
  - max_length: 応答の最大文字数
  - max_rows: 取得する最大行数

  ※LLMがパラメータの使い方を試行錯誤することが多いようです。クライアントへパラメータの使い方を上手く伝える方法があったら教えてください。
  ※読むのは LLM なのでフォーマットは余計かもしれません。

### list_tables
データベースのテーブル一覧を表示します。
- パラメータ:
  - max_rows: 取得する最大テーブル数（integer型、デフォルト: 50）
  - name_pattern: テーブル名のパターン（例: '%EMP%'）（オプション）
  - order_by: 並び順（'TABLE_NAME'または'CREATED'、デフォルト: 'TABLE_NAME'）
  - include_system_tables: システムテーブルを含めるかどうか（デフォルト: False）
  - use_all_tables: ALL_TABLESを参照するかどうか（デフォルト: False）
  - owner: テーブルの所有者（use_all_tablesがTrueの場合は必須）

### describe_table
テーブルの構造を表示します。sqlplus の describe を模しています。
- パラメータ:
  - table_name: テーブル名

### oracle_query_assistant
execute_oracle（Oracle Databaseへのクエリ実行）をガイドするプロンプトを返します。

- パラメータ
  - query_type: SQL のタイプ（現在は、"select"のみ）

## 使用方法

### MCPクライアントへの登録:
Claude Desktop や Cursor の MCP 設定ファイルに以下を追加します。
```json
{
  "mcpServers": {
    "ORACLE": {
      "command": "仮想環境の Python 実行ファイルへの絶対パス（...\\mcp-server-for-autonomous-database\\.venv\\Scripts\\python.exe）",
      "args": [
        "MCPサーバーの絶対パス（....\\mcp-server-for-oracle-database\\oracledb_mcp_server.py）"
      ]
    }
  }
}
```
※構成ファイルを変更した後は、MCPクライアントの再起動が必要です。Claude Desktop の場合、バックグラウンドで動いているプロセスも一度停止してから再起動してください。
### Claude Desktop や Cursor 等の MCP クライアントでいろいろお試しください。
#### 例1: テーブルの構造を表示
```text
xxxx テーブルの構造をしらべて
```
```text
xxxx のスキーマは
```
![スクリーンショット](screenshot_sample-01.jpg)

#### 例2: テーブルのデータを取得
```text
xxxx テーブルのデータを取得して
```
![スクリーンショット](screenshot_sample-02.jpg)
![スクリーンショット](screenshot_sample-03.jpg)
![スクリーンショット](screenshot_sample-04.jpg)
#### 例3: SQL の実行
```text
この SQL を試してみて
```


## セキュリティ

- SELECT 文以外は受け付けません（DDL/DMLは実行できません）
  - SELECT INTO と UNION ALL も受け付けません
- クエリ長の制限（デフォルト: 1MB）
- 危険なキーワードのチェック
- 入力値のサニタイズ
- 読み取り専用クエリの検証
pymes-api 0.2.2
A Python library for Facebook Messenger API
Requires Python: >=3.10

# pymes

A simple, lightweight Python wrapper for the Facebook Messenger API.

## Installation

No installation command is available yet as this package is not yet published to PyPI. 
Once published, you will be able to install it via pip:

```bash
pip install pymes-api
```

## Usage

### Basic Example

```python
from pymes import MessengerClient, Text, Attachment

# Initialize the client
sender = MessengerClient(page_access_token="YOUR_PAGE_ACCESS_TOKEN")

# Send a text message
sender.send(recipient_id="USER_ID", message=Text("Hello, world!"))

# Send an attachment (Image)
sender.send("USER_ID", Attachment("image", "https://example.com/image.jpg"))

# Mark as seen
sender.send("USER_ID", action="mark_seen")
```

### Supported Message Types

- `Text`: Simple text messages.
- `Attachment`: Images, files, audio, video.
- `QuickReply`: Messages with quick reply buttons.
- `GenericTemplate`: Carousel-like templates with images and buttons.

## Django Support (New)

You can easily handle incoming messages using the `MessengerView`.

```python
# views.py
from pymes.adapter.django import MessengerView

class BotView(MessengerView):
    verify_token = "YOUR_VERIFY_TOKEN"
    app_id = "YOUR_PAGE_ID" # Optional verification

    def handle_message(self, metadata):
        sender_id = metadata['sender_id']
        message = metadata['payload']
        print(f"Message from {sender_id}: {message}")

    # handle any event defining a method with the event name like handle_{event name}
    

# urls.py
from django.urls import path
from .views import BotView

urlpatterns = [
    path("webhook/", BotView.as_view()),
]
```

## Requirements

- Python 3.10+
- `requests` library

## License

MIT License