semvec/pypi-packages huggingface dataset:
Cell-BLAST 0.5.1
Single-cell transcriptome querying tool
Requires Python: >=3.6
Keywords: bioinformatics, deep-learning, single-cell

# Cell BLAST

[![license-badge](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![pypi-badge](https://img.shields.io/pypi/v/Cell-BLAST)](https://pypi.org/project/Cell-BLAST)
[![docs-badge](https://readthedocs.org/projects/cblast/badge/?version=latest)](https://cblast.readthedocs.io/en/latest/?badge=latest)
[![build-badge](https://github.com/gao-lab/Cell_BLAST/actions/workflows/build.yml/badge.svg)](https://github.com/gao-lab/Cell_BLAST/actions/workflows/build.yml)

Cell BLAST is a cell querying tool for single-cell transcriptomics data.

For each query cell, it searches for most similar cells in the reference database.
Annotations in reference cells, e.g. cell type, can then be transfered to query
cells based on cell-to-cell similarities. See our
[publication](https://www.nature.com/articles/s41467-020-17281-7) for details.

## Installing the Python package

We only support installation via pip right now.

Installation within virtual environments are recommended, see
[virtualenv](https://virtualenv.pypa.io/en/latest/) or
[conda](https://conda.io/docs/user-guide/tasks/manage-environments.html).

For conda, here's a one-liner to set up an empty environment
for installing Cell BLAST:

`conda create -n cb python=3.9 && conda activate cb`

Then follow the instructions below to install Cell BLAST:

1. Install Cell BLAST from PyPI by running:

   `pip install Cell-BLAST`

   Or, install an editable dev version by running the following command
   under the root directory of this repo:

   `flit install -s`

2. Check if the package can be imported in the Python interpreter:

   ```python
   import Cell_BLAST as cb
   print(cb.__version__)
   ```

## Documentation

Online documentation can be found [here](https://cblast.readthedocs.org/).

## Web-based interface

We also provide a [Web-based service](http://cblast.gao-lab.org/) for
off-the-shelf querying of our ACA reference panels.

## Reproduce results in the paper

To reproduce results, please check out the `rep` branch.

## Contact

Feel free to submit an issue or contact us at
[cblast@mail.cbi.pku.edu.cn](mailto:cblast@mail.cbi.pku.edu.cn)
for problems about the Python package, website or database.
garminmaps 0.0.8
SDK for generating interactive leaflet.js maps from Garmin data.
Requires Python: >=3.8

## Overview
garminmaps is an SDK for generating interactive leaflet.js maps from Garmin data.

## Installation
``` 
pip3 install garminmaps
```

## Example usage
```
import garminmaps

"""Example: Plot all runs from June 2024 onto a leaflet.js map."""

# Login to Garmin Connect with OAuth2
garmin_client = garminmaps.login()

# Create a new empty leaflet.js map
running_map = garminmaps.create_map()

# Get data for all runs in June 2024
activites = garminmaps.get_activities(garmin_client, "running", "2024-06-01", "2024-06-30")
for activity in activites:
    update_map(activity, running_map, "blue")

# Write the leaflet.js map to disk
running_map.save("runs.html")
```

## Contributing
Creating a dev environment:
1. Clone this repository.
2. `python3 -m venv .venv`
3. `source .venv/bin/activate`
4. `pip3 install .`

Commiting code:
1. `ruff format && ruff check`
2. Fork the repository, checkout a new branch on your forked version, and push changes.
3. Open a pull request in the [GitHub repository](https://github.com/doorlay/garminmaps/pulls).

Building & releasing to PyPI (author only):
1. Bump the version of the project in `pyproject.toml`.
2. `python3 -m build`
3. To release to TestPyPI: `python3 -m twine upload --repository testpypi dist/*`
4. To release to PyPI: `python3 -m twine upload dist/*`

<!-- ## Future Work
- Add support for range-based plotting
- Superimpose activity data onto the graph
- Use Wails to turn this into an actual application. Use in-browser SSO.
- Drop down menu in the upper left for each type of activity, color-coded. When you select a type, only those types are displayed
- For each activity type, group activities in a similar location and allow selection of that location. When selected, navigate to that region on the map.
- For each activity, display information on click. e.g. when you click on a run, you get distance, pace, bpm, calories burned, etc. 
- hand-roll GPX parsing to lower dependencies. Maybe the same for mapping, auth -->
aipmai-tools 0.4.26
Set of tools for the crewAI framework (Chinese Version)
Requires Python: <=3.13,>=3.10

<div align="center">

![crewAI 的 Logo，两个人在一艘船上划船](./assets/crewai_logo.png)

<div align="left">

# **crewAI 工具**
本文档全面介绍了如何为 [crewAI](https://github.com/aithoughts/aipmAI) 代理设置复杂的工具，方便创建定制工具以增强您的 AI 解决方案。

在 CrewAI 代理领域，工具对于增强功能至关重要。本指南概述了为您的代理配备一系列现成工具的步骤，以及创建您自己的工具的方法。

</div>

<h3>

[主页](https://www.theforage.cn/) | [aipmAI - crewAI 中文解决方案](https://aipm-docs.theforage.cn/) | [与文档聊天](https://chatg.pt/DWjSBZn) | [示例](https://github.com/aithoughts/aipmAI-examples) | [Discord](https://discord.com/invite/X4JWnZnxPb)

</h3>

</div>

## 目录

- [创建您的工具](#创建您的工具)
	- [继承 `BaseTool`](#继承-basetool)
	- [使用 `tool` 装饰器](#使用-tool-装饰器)
- [贡献指南](#贡献指南)
- [开发设置](#开发设置)

## 创建您的工具

工具始终应返回字符串，因为它们旨在供代理用于生成响应。

创建 crewAI 代理工具的方法有三种：
- [继承 `BaseTool`](#继承-basetool)
- [使用 `tool` 装饰器](#使用-tool-装饰器)

### 继承 `BaseTool`

```python
from crewai_tools import BaseTool

class MyCustomTool(BaseTool):
    name: str = "我的工具名称"
    description: str = "对该工具用途的清晰描述，您的代理将需要此信息才能使用它。"

    def _run(self, argument: str) -> str:
        # 实现代码在此处
        pass
```

定义一个继承自 `BaseTool` 的新类，指定 `name`、`description` 和用于操作逻辑的 `_run` 方法。


### 使用 `tool` 装饰器

对于更简单的方法，请直接使用所需的属性和功能逻辑创建 `Tool` 对象。

```python
from crewai_tools import tool
@tool("我的工具名称")
def my_tool(question: str) -> str:
    """对该工具用途的清晰描述，您的代理将需要此信息才能使用它。"""
    # 函数逻辑在此处
```

`tool` 装饰器简化了流程，以最小的开销将函数转换为工具。

## 贡献指南

我们热烈欢迎您为丰富此工具集做出贡献。要做出贡献：

1. **Fork 仓库：**首先将仓库 fork 到您的 GitHub 帐户。
2. **功能分支：**在您的 fork 中为功能或改进创建一个新分支。
3. **实现您的功能：**将您的贡献添加到新分支中。
4. **拉取请求：**从您的功能分支向主仓库提交拉取请求。

我们非常感谢您的贡献，这将有助于增强此项目。

## **开发设置**

**安装依赖项：**

```bash
poetry install
```

**激活虚拟环境：**

```bash
poetry shell
```

**设置预提交钩子：**

```bash
pre-commit install
```

**运行测试：**

```bash
poetry run pytest
```

**静态类型检查：**

```bash
poetry run pyright
```

**打包：**

```bash
poetry build
```

**本地安装：**

```bash
pip install dist/*.tar.gz
```

感谢您有兴趣通过高级工具增强 AI 代理的功能。您的贡献将产生重大影响。
kblpbp 1.0.1
Web scraping and visualization tools for Korean Basketball League's play-by-play data
Requires Python: >=3.6

While replicating the high-quality PBP data of leagues like the NBA, WNBA, and NCAA for the KBL can be challenging, there are still alternative methods to compile such data. One approach involves utilizing web scraping techniques(i.e., Selenium) to extract information from real-time text updates provided by KBL and platforms like ‘NAVER.’ These updates via text offer descriptions of plays, which allow us to have a rudimentary form of PBP data for further analysis and study after cleansing. By using such form of data, the project aims to demonstrate the types of analysis that can be conducted in the KBL.
ampur 0.1.0
This program profiles according to the standards set by BRL implemented by GDE
Requires Python: <4.0,>=3.12

# Ampur





#######################    Adding New Learners    ####################### 
Ensure that the imported file has:
    Only one sheet
    Columns                                                                                         # very important, verbatim
        SenPha: 'First Name', Surname, ID No., Home Language, Grade, Class (Only)
        FET: First Name, Surname, ID/Passport Number, Home Language, Stream (A, B, C, etc.), Math Type (A or B)
                                                    # streams are set at the beginning and saved as presets

        

#######################    Adding New Learners    #######################




#######################    Removing Learners    #######################
Ensure that the imported file has:
    Only one sheet
    Columns 
        First Name, Surname, ID/Passport Number, Grade, Class