semvec/pypi-packages huggingface dataset:
bbscripts 0.1.0
A collection of reusable utility functions and modules.
Requires Python: >=3.10
Keywords: bblab, bitbytelab, python, utility, utils


<p><div align="center">
  <img src="assets/bitbytelab.png" alt="BitByteLab Logo" height="100">
 

**A Collection of reusable utilities.**

[![Release](https://img.shields.io/github/v/tag/bitbytelab/bblab)](https://github.com/bitbytelab/bblab/tag)
[![Platforms](https://img.shields.io/badge/platform-windows%20%7C%20macOS%20%7C%20linux-blue)]()
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](./LICENSE)
[![Python](https://img.shields.io/badge/Python-3.9%2B-blue.svg)](https://www.python.org/)
[![PyPI](https://img.shields.io/badge/PyPI-upwork-cli-lightgrey.svg)](https://pypi.org/project/upwork-cli)

</div></p>

bblab.utils
=============================================

A collection of reusable utility functions and modules.

Usage
=====

---
## 🧪 Project Structure

<pre>
<!-- dir-tree-start -->
📁 bblab/
├── 📁 src/
│   └── 📁 bblab/
├── 📁 examples/
│   └── sample_usage.py
├── 📁 tests/
│   └── test.py
├── ⚙️ .env
├── 🚫 .gitignore
├── 📃 LICENSE
├── 📃 LICENSE.txt
├── ⚙️ pyproject.toml
├── 📝 README.md
└── ⚙️ ruff.toml
<!-- dir-tree-end -->
</pre>

---

## 📄 License

Licensed under the [MIT License](LICENSE).

---

## 🤝 Contributing

- Open an issue for ideas, bugs, or suggestions.
- Pull requests are welcome!

---

## 🔗 Links

- 📦 [PyPI](https://pypi.org/project/bblab)
- 🛠️ [Issues](https://github.com/bitbytelab/bblab/issues)
- ⭐ [Star on GitHub](https://github.com/bitbytelab/bblab)

---
bbextras 0.1.0
A collection of reusable utility functions and modules.
Requires Python: >=3.10
Keywords: bblab, bitbytelab, python, utility, utils


<p><div align="center">
  <img src="assets/bitbytelab.png" alt="BitByteLab Logo" height="100">
 

**A Collection of reusable utilities.**

[![Release](https://img.shields.io/github/v/tag/bitbytelab/bblab)](https://github.com/bitbytelab/bblab/tag)
[![Platforms](https://img.shields.io/badge/platform-windows%20%7C%20macOS%20%7C%20linux-blue)]()
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](./LICENSE)
[![Python](https://img.shields.io/badge/Python-3.9%2B-blue.svg)](https://www.python.org/)
[![PyPI](https://img.shields.io/badge/PyPI-upwork-cli-lightgrey.svg)](https://pypi.org/project/upwork-cli)

</div></p>

bblab.utils
=============================================

A collection of reusable utility functions and modules.

Usage
=====

---
## 🧪 Project Structure

<pre>
<!-- dir-tree-start -->
📁 bblab/
├── 📁 src/
│   └── 📁 bblab/
├── 📁 examples/
│   └── sample_usage.py
├── 📁 tests/
│   └── test.py
├── ⚙️ .env
├── 🚫 .gitignore
├── 📃 LICENSE
├── 📃 LICENSE.txt
├── ⚙️ pyproject.toml
├── 📝 README.md
└── ⚙️ ruff.toml
<!-- dir-tree-end -->
</pre>

---

## 📄 License

Licensed under the [MIT License](LICENSE).

---

## 🤝 Contributing

- Open an issue for ideas, bugs, or suggestions.
- Pull requests are welcome!

---

## 🔗 Links

- 📦 [PyPI](https://pypi.org/project/bblab)
- 🛠️ [Issues](https://github.com/bitbytelab/bblab/issues)
- ⭐ [Star on GitHub](https://github.com/bitbytelab/bblab)

---
bbextra 0.1.0
A collection of reusable utility functions and modules.
Requires Python: >=3.10
Keywords: bblab, bitbytelab, python, utility, utils


<p><div align="center">
  <img src="assets/bitbytelab.png" alt="BitByteLab Logo" height="100">
 

**A Collection of reusable utilities.**

[![Release](https://img.shields.io/github/v/tag/bitbytelab/bblab)](https://github.com/bitbytelab/bblab/tag)
[![Platforms](https://img.shields.io/badge/platform-windows%20%7C%20macOS%20%7C%20linux-blue)]()
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](./LICENSE)
[![Python](https://img.shields.io/badge/Python-3.9%2B-blue.svg)](https://www.python.org/)
[![PyPI](https://img.shields.io/badge/PyPI-upwork-cli-lightgrey.svg)](https://pypi.org/project/upwork-cli)

</div></p>

bblab.utils
=============================================

A collection of reusable utility functions and modules.

Usage
=====

---
## 🧪 Project Structure

<pre>
<!-- dir-tree-start -->
📁 bblab/
├── 📁 src/
│   └── 📁 bblab/
├── 📁 examples/
│   └── sample_usage.py
├── 📁 tests/
│   └── test.py
├── ⚙️ .env
├── 🚫 .gitignore
├── 📃 LICENSE
├── 📃 LICENSE.txt
├── ⚙️ pyproject.toml
├── 📝 README.md
└── ⚙️ ruff.toml
<!-- dir-tree-end -->
</pre>

---

## 📄 License

Licensed under the [MIT License](LICENSE).

---

## 🤝 Contributing

- Open an issue for ideas, bugs, or suggestions.
- Pull requests are welcome!

---

## 🔗 Links

- 📦 [PyPI](https://pypi.org/project/bblab)
- 🛠️ [Issues](https://github.com/bitbytelab/bblab/issues)
- ⭐ [Star on GitHub](https://github.com/bitbytelab/bblab)

---
wadas-runtime 0.2.6
Wadas Inference Runtime
Requires Python: >=3.10
Keywords: intel core ultra, wadas, inference, runtime, openvino

# WADAS Runtime

## Description

WADAS Runtime is a library designed to facilitate inference using OpenVINO for the Wild Animals Detection and Alert System (WADAS) project. It provides tools and utilities to streamline the decryption and execution of AI models.

## Usage

To use the WADAS Runtime library, follow these steps:

1. Install the library locally:

   ```bash
   pip install wadas_runtime
   ```

2. Import the library in your Python project:

   ```python
   import wadas_runtime as wadas
   ```

3. Load and compile the model. The library will decrypt the model in real time

   ```python
   import wadas_runtime as wadas

   xml, bin = # Path to the model XML and encrypted binary file
   compiled_model = wadas.load_and_compile_model(xml, bin, "GPU")
   ```

## Developer Guide

It is suggested to install the package locally by using `pip install -e .[dev]`. OpenSSL is required to build the package and needs to be installed separately.

### Git hooks

All developers should install the git hooks that are tracked in the `.githooks` directory. We use the pre-commit framework for hook management. The recommended way of installing it is using pip:

```bash
pre-commit install
```

If you want to manually run all pre-commit hooks on a repository, run `pre-commit run --all-files`. To run individual hooks use `pre-commit run <hook_id>`.

Uninstalling the hooks can be done using

```bash
pre-commit uninstall
```

## Testing the library

Python test uses `pytest` library. Type

```bash
cd test && pytest
```

to run the full test suite.

### Generate Python packets

To create packets run the following commands

```bash
python -m build --sdist
cibuildwheel --platform windows --output-dir dist
```

### Publishing packets

Then check on the built `sdist` and `wheel` that are properly formatted (all files should return a green PASSED)

```bash
twine check dist/*
```

Upload the packets to `testpypi`

```bash
twine upload --repository testpypi dist/*
```

To upload them to the real index (verify first with `testpypi`)

```bash
twine upload dist/*
```
towles-tool 0.0.7
Helper cli commands from a developer
Requires Python: <4.0,>=3.9
Keywords: cli, python, towles

# towles-tool

[![Release](https://img.shields.io/github/v/release/ChrisTowles/towles-tool)](https://img.shields.io/github/v/release/ChrisTowles/towles-tool)
[![Build status](https://img.shields.io/github/actions/workflow/status/ChrisTowles/towles-tool/main.yml?branch=main)](https://github.com/ChrisTowles/towles-tool/actions/workflows/main.yml?query=branch%3Amain)
[![codecov](https://codecov.io/gh/ChrisTowles/towles-tool/branch/main/graph/badge.svg)](https://codecov.io/gh/ChrisTowles/towles-tool)
[![Commit activity](https://img.shields.io/github/commit-activity/m/ChrisTowles/towles-tool)](https://img.shields.io/github/commit-activity/m/ChrisTowles/towles-tool)
[![License](https://img.shields.io/github/license/ChrisTowles/towles-tool)](https://img.shields.io/github/license/ChrisTowles/towles-tool)


Helper cli commands from a developer

- **Github repository**: <https://github.com/ChrisTowles/towles-tool/>
- **Documentation** <https://ChrisTowles.github.io/towles-tool/>


## Installation

These instructions are to install globally using [uv](https://docs.astral.sh/uv/getting-started/installation/#standalone-installer).


### Install from pypi

https://pypi.org/project/towles-tool/

```bash

uv tool install towles-tool

```
Testing the installation was successful:
```bash
towles-tool --version

```
Or using the shortened alias `tt`

```bash
tt --version
```

### Install Autocompletion

To install autocompletion, run the following command:

```bash
towles-tool --install-completion
```

## Development

Follow the instructions in [docs/development-environment.md](docs/development-environment.md) to set up your development environment.


## Documentation

- [Releasing a new version](docs/how-to-release.md)

## Brother's Contract

- 2025-06-07: Patrick agreed that while he loves rust. he can not add it to this project until he first addes and extendsion system to do it first.


## Blog Posts

Chris Also keeps a blog where he writes about his learnings. Check it out here: https://chris.towles.dev/ and follow me on twitter: https://twitter.com/Chris_Towles
hkopenai.hk-finance-mcp-server 0.1.7
Hong Kong Finance MCP Server providing financial data tools
Requires Python: >=3.7

# Hong Kong Finance Data MCP Server

[![GitHub Repository](https://img.shields.io/badge/GitHub-Repository-blue.svg)](https://github.com/hkopenai/hk-finance-mcp-server)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

This is an MCP server that provides access to finance related data in Hong Kong through a FastMCP interface.

## Features

1. Monthly statistics on the number of new and active business registrations in Hong Kong
2. Quarterly statistics on residential mortgage loans in negative equity in Hong Kong
3. Credit card lending survey results in Hong Kong
4. Coin cart schedule in Hong Kong
5. Get list of hotlines for reporting loss of credit card from Hong Kong banks
6. Get information of Tender Invitation and Notice of Award of Contracts from Hong Kong Monetary Authority

## Examples

* What is the number of new business registered in Hong Kong 2024?
* What is the negative loan situation in Hong Kong Q1 2025 compare with Q1 2024?
* Write a commentary about the latest residential mortgage loans in negative equity in Hong Kong
* How is current Hong Kong economy by referencing credit lending data and residential mortgage loans in negative equity?

Assume chart tool is available:

* Plot a line chart showing trend and number of new business registered each month from Jan to Dec in Hong Kong 2024.
![](https://raw.githubusercontent.com/hkopenai/hk-finance-mcp-server/refs/heads/main/assets/line_chart.png)

## Data Source

* Hong Kong Monetary Authority
* Hong Kong Inland Revenue Department

## Setup

1. Clone this repository
2. Install Python dependencies:
   ```bash
   pip install -r requirements.txt
   ```
3. Run the server:
   ```bash
   python app.py
   ```

### Running Options

- Default stdio mode: `python app.py`
- SSE mode (port 8000): `python app.py --sse`

## Cline Integration

To connect this MCP server to Cline using stdio:

1. Add this configuration to your Cline MCP settings (cline_mcp_settings.json):
```json
{
  "hk-finance": {
    "disabled": false,
    "timeout": 3,
    "type": "stdio",
    "command": "uvx",
    "args": [
      "hkopenai.hk-finance-mcp-server"
    ]
  }
}
```

## Testing

Tests are available in the `tests/` directory. Run with:
```bash
pytest
```
epimodels 0.5.3
Library of mathematical epidemic models for use in simulation studies and inference.
Requires Python: >=3.12


# Epimodels



This library a simple interface to simulate mathematical epidemic models.
 


## Getting started


Simple SIR simulation

```python
from epimodels.continuous.models import SIR

model = SIR()
model([1000, 1, 0], [0, 50], 1001, {'beta': 2, 'gamma': .1})
model.plot_traces()
```


### Related libraries

For stochastic epidemic models check [this](https://github.com/fccoelho/EpiStochModels).
django-gcloud-connectors 1.5.0
A Django library for connecting to Google Cloud Datastore and Firestore from Python 3 runtimes.
Keywords: Google Cloud Datastore, Google App Engine, Django

# Django GCloud Connectors (gcloudc)

Django Google Cloud Connectors provides database backends for two non-relational database services that run on Google Cloud:

 - Google Cloud Datastore
 - Google Cloud Firestore

This django-gcloud-connectors project allows you to seamlessly use the Django ORM with these databases; allowing you to leverage
the full power of Django on a massively scalable No-SQL database.

For more information on the project, please see the [documentation](https://potato-oss.gitlab.io/google-cloud/django-gcloud-connectors/)

If you are interested in submitting a patch, please refer to the [Contributing](https://potato-oss.gitlab.io/google-cloud/django-gcloud-connectors/contributing) page.

---

## Looking for Commercial Support?

Potato offers Commercial Support for all its Open Source projects and we can tailor a support package to your needs.

If you're interested in commercial support, training, or consultancy then go ahead and contact us at [opensource@potatolondon.com](mailto:opensource@potatolondon.com)
openaihk.hk-finance-mcp-server 0.1.7
Hong Kong Finance MCP Server providing financial data tools
Requires Python: >=3.7

# Hong Kong Finance Data MCP Server

[![GitHub Repository](https://img.shields.io/badge/GitHub-Repository-blue.svg)](https://github.com/hkopenai/hk-finance-mcp-server)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

This is an MCP server that provides access to finance related data in Hong Kong through a FastMCP interface.

## Features

1. Monthly statistics on the number of new and active business registrations in Hong Kong
2. Quarterly statistics on residential mortgage loans in negative equity in Hong Kong
3. Credit card lending survey results in Hong Kong
4. Coin cart schedule in Hong Kong
5. Get list of hotlines for reporting loss of credit card from Hong Kong banks
6. Get information of Tender Invitation and Notice of Award of Contracts from Hong Kong Monetary Authority

## Examples

* What is the number of new business registered in Hong Kong 2024?
* What is the negative loan situation in Hong Kong Q1 2025 compare with Q1 2024?
* Write a commentary about the latest residential mortgage loans in negative equity in Hong Kong
* How is current Hong Kong economy by referencing credit lending data and residential mortgage loans in negative equity?

Assume chart tool is available:

* Plot a line chart showing trend and number of new business registered each month from Jan to Dec in Hong Kong 2024.
![](https://raw.githubusercontent.com/hkopenai/hk-finance-mcp-server/refs/heads/main/assets/line_chart.png)

## Data Source

* Hong Kong Monetary Authority
* Hong Kong Inland Revenue Department

## Setup

1. Clone this repository
2. Install Python dependencies:
   ```bash
   pip install -r requirements.txt
   ```
3. Run the server:
   ```bash
   python app.py
   ```

### Running Options

- Default stdio mode: `python app.py`
- SSE mode (port 8000): `python app.py --sse`

## Cline Integration

To connect this MCP server to Cline using stdio:

1. Add this configuration to your Cline MCP settings (cline_mcp_settings.json):
```json
{
  "hk-finance": {
    "disabled": false,
    "timeout": 3,
    "type": "stdio",
    "command": "uvx",
    "args": [
      "openaihk.hk-finance-mcp-server"
    ]
  }
}
```

## Testing

Tests are available in the `tests/` directory. Run with:
```bash
pytest
```
python-seatsurfing 0.4.1
Python client to interface with Seatsurfing
Requires Python: >=3.9

# python-seatsurfing

A Python client and library to interact with the [Seatsurfing](https://github.com/seatsurfing/) API.

> [!IMPORTANT]
> The library is a work in progress, not all functionality is available yet, or finalized.

## Installation

```sh
pip install python-seatsurfing
```

## Usage

Usage with known organization ID and credentials:

```py
from datetime import datetime
import seatsurfing

# Create client with authentication information
client = seatsurfing.Client(
    base_url="https://seatsurfing.example.com",
    organization_id = "9a2184f9-671f-440b-81f0-18e217af34f8",
    username="admin@seatsurfing.local",
    password="12345678",
)

# Get bookings for the next 30 days
from_date = datetime.today()
to_date = datetime.today() + timedelta(days=30)
bookings = client.booking.get_filtered_org_bookings(from_date, to_date)

print(bookings)
```

Usage with fetching data dynamically:

```py
from datetime import datetime
import seatsurfing

# Create unauthenticated client
client = seatsurfing.Client(base_url="https://seatsurfing.example.com")
# Fetch organization information
org = client.authentication.get_singleorg()

# Authenticate to the organization
client.login(organization_id=org.organization.id, username="admin@seatsurfing.local", password="1234678")

# Get bookings for the next 30 days
from_date = datetime.today()
to_date = datetime.today() + timedelta(days=30)
bookings = client.booking.get_filtered_org_bookings(from_date, to_date)

print(bookings)
```
permalint 0.1.15
Lint URLs
Requires Python: >=3.9

# permalint

Lint URLs (mostly for teaxyz/chai, but hopefully other uses too)

## Features

- Ignores protocol (http, https, etc.)
- Normalizes GitHub URLs to owner/repo
- Removes query strings and fragments
- Lowercases domains and removes www

## Usage

```python
from permalint import normalize_url

url = "https://github.com/user/repo?utm_source=foo#readme"
print(normalize_url(url))  # Output: github.com/user/repo
```

## Development

- Install dependencies: `pkgx rye sync`
- Run tests: `pkgx rye run pytest`
- Lint: `pkgx ruff check src/`
- Type check: `pkgx ty src/`

## Contributing / Wishlist

- `guess-canonical-url` to guess the correct URL based on a passed list of URLs
- actual source of Homepages for
aiwang-indicator 0.1.6
aiwang-indicator 是一个采用通达信指标接口的 Python 技术指标编辑公式库。用户可以像在通达信中一样,使用简洁的TDX style语法进行各类技术指标的编写与回测,非常适合量化研究和策略开发。
Keywords: 通达信指标, TDX, 技术指标, 量化


**aiwang-indicator** 是一个采用类似通达信指标接口的 Python 技术指标编辑公式库。用户可以像在通达信中一样，使用简洁的TDX style语法进行各类技术指标的编写与回测，非常适合量化研究和策略开发。

> **说明：本项目中的部分代码来自开源项目 [MyTT](https://github.com/mpquant/MyTT)，特此致谢。**

---

## 目录

- [特性](#特性)
- [安装](#安装)
- [快速开始](#快速开始)
- [进阶用法](#进阶用法)
- [贡献与反馈](#贡献与反馈)

---

## 特性

- 通达信风格的指标函数接口，极易上手
- 支持主流金融数据加载（默认采用AkShare）
- 丰富的常用指标函数，支持自定义扩展
- 兼容 numpy/pandas，便于数据分析

---

## 安装 aiwang-indicator

```bash
pip install aiwang-indicator
```

---

## 快速开始

以下是一个简单示例，演示如何使用 **aiwang-indicator** 加载数据并计算指标：

### 1. 数据加载与环境初始化

```python
from aiwang_indicator import set_data_loader
from aiwang_indicator.data.loader.ak_loader import AkLoader

# 初始化数据加载器
data_loader = AkLoader(start_date='20240101')
set_data_loader(data_loader, default_stock_id="600900", default_freq='daily')
```

### 2. 常用行情数据序列变量

#### 默认行情数据序列

| 变量        | 含义         |
|-------------|--------------|
| `CLOSE()`/`C` | 默认收盘价序列 |
| `OPEN()`/`O`  | 默认开盘价序列 |
| `HIGH()`/`H`  | 默认最高价序列 |
| `LOW()`/`L`   | 默认最低价序列 |
| `DATE()`/`D`  | 默认日期序列      |

#### 带参数行情数据序列

| 函数         | 说明                         |
|--------------|------------------------------|
| `CLOSE('代码')` | 获取指定股票的收盘价序列 |
| `OPEN('代码')`  | 获取指定股票的开盘价序列 |
| `HIGH('代码')`  | 获取指定股票的最高价序列 |
| `LOW('代码')`   | 获取指定股票的最低价序列 |
| `DATE('代码')`  | 获取指定股票的日期序列   |
| `CLOSE('周期')` | 获取指定周期的收盘价序列 |
| `OPEN('周期')`  | 获取指定周期的开盘价序列 |
| `HIGH('周期')`  | 获取指定周期的最高价序列 |
| `LOW('周期')`   | 获取指定周期的最低价序列 |
| `DATE('周期')`  | 获取指定周期的日期序列   |
| `CLOSE('代码', '周期')`          | 获取指定股票指定周期的收盘价序列<br>如：`CLOSE('600519', 'weekly')` 获取600519的周线收盘价 |
| `OPEN('代码', '周期')`           | 获取指定股票指定周期的开盘价序列<br>如：`OPEN('600519', 'weekly')` 获取600519的周线开盘价   |
| `HIGH('代码', '周期')`           | 获取指定股票指定周期的最高价序列<br>如：`HIGH('600519', 'weekly')` 获取600519的周线最高价   |
| `LOW('代码', '周期')`            | 获取指定股票指定周期的最低价序列<br>如：`LOW('600519', 'weekly')` 获取600519的周线最低价     |
| `DATE('代码', '周期')`           | 获取指定股票指定周期的日期序列<br>如：`DATE('600519', 'weekly')` 获取600519的周线日期       |


### 3. 指标函数示例

**计算指数化序列**

```python
from aiwang_indicator import *

idx = INDEX(C)  # 将收盘价序列指数化，首日为1000
```

**计算 KDJ 指标**

```python
from aiwang_indicator import *

N = 9
M1 = 3
M2 = 3

RSV = (C - LLV(L, N)) / (HHV(H, N) - LLV(L, N)) * 100
K = SMA(RSV, M1, 1)
D = SMA(K, M2, 1)
J = 3 * K - 2 * D
```

**直接获取数据序列**

```python
from aiwang_indicator import *

close_prices = CLOSE()           # 获取默认股票的收盘价序列
open_prices = OPEN('600519')     # 获取指定股票的开盘价序列
close_prices = CLOSE('600519', 'weekly')        #获取600519的周线收盘价
```

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## 进阶用法

- 支持自定义数据加载器
- 支持多周期、多标的切换
- 可与 pandas/numpy 等生态无缝结合

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## 贡献与反馈

欢迎提交 Issue 或 PR，完善指标库与文档！