semvec/pypi-packages huggingface dataset:
hh-jira-mcp-server 0.1.0
A MCP server project
Requires Python: >=3.13

# hh-jira-mcp-server MCP server

A MCP server project

## Components

### Resources

The server implements a simple note storage system with:
- Custom note:// URI scheme for accessing individual notes
- Each note resource has a name, description and text/plain mimetype

### Prompts

The server provides a single prompt:
- summarize-notes: Creates summaries of all stored notes
  - Optional "style" argument to control detail level (brief/detailed)
  - Generates prompt combining all current notes with style preference

### Tools

The server implements one tool:
- add-note: Adds a new note to the server
  - Takes "name" and "content" as required string arguments
  - Updates server state and notifies clients of resource changes

## Configuration

[TODO: Add configuration details specific to your implementation]

## Quickstart

### Install

#### Claude Desktop

On MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`
On Windows: `%APPDATA%/Claude/claude_desktop_config.json`

<details>
  <summary>Development/Unpublished Servers Configuration</summary>
  ```
  "mcpServers": {
    "hh-jira-mcp-server": {
      "command": "uv",
      "args": [
        "--directory",
        "/Users/adubinin/IdeaProjects/hh-jira-mcp-server",
        "run",
        "hh-jira-mcp-server"
      ]
    }
  }
  ```
</details>

<details>
  <summary>Published Servers Configuration</summary>
  ```
  "mcpServers": {
    "hh-jira-mcp-server": {
      "command": "uvx",
      "args": [
        "hh-jira-mcp-server"
      ]
    }
  }
  ```
</details>

## Development

### Building and Publishing

To prepare the package for distribution:

1. Sync dependencies and update lockfile:
```bash
uv sync
```

2. Build package distributions:
```bash
uv build
```

This will create source and wheel distributions in the `dist/` directory.

3. Publish to PyPI:
```bash
uv publish
```

Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token: `--token` or `UV_PUBLISH_TOKEN`
- Or username/password: `--username`/`UV_PUBLISH_USERNAME` and `--password`/`UV_PUBLISH_PASSWORD`

### Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging
experience, we strongly recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector).


You can launch the MCP Inspector via [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) with this command:

```bash
npx @modelcontextprotocol/inspector uv --directory /Users/adubinin/IdeaProjects/hh-jira-mcp-server run hh-jira-mcp-server
```


Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
openSIMS 0.7.1
A Python package for SIMS data reduction
Requires Python: >=3.8

# openSIMS

Python package for SIMS data reduction

## Installation

```
python -m pip install openSIMS --upgrade
```

## Usage

From the Python REPL:

```
import openSIMS as S
S.gui()
```

Click on the 'Log' button of the GUI to see what's going on.

Example data are provided in the [data](https://github.com/pvermees/openSIMS/tree/main/data) folder of the GitHub repository.
tga-safe-oper-bsd 0.1.6
A small example package
Requires Python: >=3.0

# tga安全用ezconfig去查询tga的程序

## 使用方法

```text
pip install tga-safe-oper-bsd
```

传入自定义参数，获取数据

```python
from tga_safe.query import Query
import pandas as pd
from io import StringIO
q = Query(env="xx", app_id="xxxx", secret="xxxx", url="xxxxxxx")
res = q.fetch_data(sql="""select field1, field2  from xxx limit 10""")
column_names = ['field1', 'field2']
data_io = StringIO(res)
df = pd.read_csv(data_io, encoding='utf-8', header=None, names=column_names)
print(df)
```



环境依赖：

```text
ezconfig-client==0.7
```

**测试参考代码**

python test.py

## 版本说明

| 版本  | 变更                                                        |
|-----|-----------------------------------------------------------|
| 0.1.5 | 从tga拉取sql数据                                 |
cycarla-backend 0.1.12
Backend for Cycarla
Requires Python: <3.11.0,>=3.10.0

`cycarla-backend` is a Python Flask server that serves as the backend to [CYCARLA](https://github.com/tensorturtle/cycarla)

The three components of Cycarla are:
1. [CARLA](https://github.com/carla-simulator/carla) - An open-source simulator for autonomous driving research.
2. [cycarla_backend](https://github.com/tensorturtle/cycarla/tree/main/cycarla-backend) - This Python Flask server which links the frontend to CARLA.
3. [cycarla_frontend](https://github.com/tensorturtle/cycarla/tree/main/cycarla-frontend) - A Javascript (Next.js) front-end which presents a web-based interface from your browser.

# Installation

Supported platforms: Windows 10, Ubuntu 22.04. Other versions can work if you install Python 3.10 and pipx.

## Windows 10-specific Prerequisites

If you are on Ubuntu 22.04, skip ahead to the next section. Windows needs a couple of things to be set up beforehand.

### [**1. Install Python 3.10**](https://www.python.org/downloads/release/python-31011)

Scroll to the bottom and download the 'Windows Installer (64-bit)'.

At the installer, make sure to enable the bottom option "Add python.exe to PATH"

### [**2. Install Scoop**](https://scoop.sh/)

## Install using `pipx`

`cycarla-backend` is a CLI package that is developed with [poetry](https://python-poetry.org/) and published on [pypi](https://pypi.org/project/cycarla-backend/).

We'll use `pipx` to run it in an isolated python environment.

### [**Install `pipx`**](https://github.com/pypa/pipx#install-pipx)

Follow relevant instructions for your platform

### **Install cycarla-backend** using `pipx`
```
pipx install cycarla-backend
```
Note the dash (minus) sign.

# Run App

In your terminal (Ubuntu) or Powershell (Windows):
```
cycarla_backend
```
Note the underscore.

On Windows, Allow firewall permissions when prompted.r Cycoutput including:
```
 * Running on http://127.0.0.1:9000
```

This app will receive web requests from the CYCARLA Frontend which should run at localhost port 3000, and communicate with the Python API of a local CARLA simulator whose default port is 2000.

You should start the CARLA and frontend applications next, if they haven't been started already.

See [CYCARLA top-level project README](https://github.com/tensorturtle/cycarla) for more information


# Compatibility

+ Currently, Windows 10 and Ubuntu 22.04 are the officially supported OSes for the CYCARLA project. Mac is not supported because CARLA can't run on it.
+ It is possible to run CARLA and this backend on two different computers, but it is very slow (~5 FPS).
americansouth 0.2.3
Monitor internet data usage to avoid overage charges
Requires Python: >=3.9

# Americansouth

Motivation: Monitor internet data usage to avoid unexpected overage charges from Astound.

## Usage

The tool processes data usage information from a JSON file in this format:

```json
[
  {
    "date": "2024-11-13",
    "amount": 79.13,
    "amountUnits": "GB",
    "total": 400,
    "totalUnits": "GB",
    "overage": 0,
    "overageUnits": "GB",
    "scrapedAt": "2024-11-13T06:17:28.611Z"
  },
  {
    "date": "2024-11-13",
    "amount": 79.13,
    "amountUnits": "GB",
    "total": 400,
    "totalUnits": "GB",
    "overage": 0,
    "overageUnits": "GB",
    "scrapedAt": "2024-11-13T06:41:24.588Z"
  }
]
```

Run the script by passing the JSON file:

```bash
americansouth data.json
```

Example output:

```
  DAILY USED DAILY BUDGET   TOTAL USED MONTHLY BUDGET      TOTAL DATA FETCH TIME
--------------------------------------------------------------------------------------------
        61GB         16GB         61GB          338GB      400GB Sat Nov 09 11:58 pm 2024
         5GB         17GB         66GB          333GB      400GB Mon Nov 11 07:49 am 2024
         5GB         17GB         71GB          328GB      400GB Mon Nov 11 09:12 pm 2024
         7GB         18GB         79GB          320GB      400GB Tue Nov 12 10:41 pm 2024
         6GB         18GB         85GB          314GB      400GB Wed Nov 13 08:07 pm 2024
         8GB         19GB         93GB          306GB      400GB Thu Nov 14 04:25 pm 2024
        14GB         19GB        107GB          292GB      400GB Fri Nov 15 08:17 am 2024
        12GB         20GB        120GB          279GB      400GB Sun Nov 17 07:59 am 2024
         7GB         22GB        127GB          272GB      400GB Mon Nov 18 07:52 am 2024
         5GB         23GB        133GB          266GB      400GB Tue Nov 19 07:37 am 2024
        14GB         22GB        147GB          252GB      400GB Tue Nov 19 01:43 pm 2024
```

The output shows:

- Daily data usage
- Recommended daily budget to stay within monthly limit
- Total data used so far
- Remaining monthly budget
- Total monthly allocation
- Timestamp of when data was fetched
cgpa-calculator 2.2.0
A Python-based CGPA Calculator to manage courses and calculate weighted CGPA.
Requires Python: >=3.6

# CGPA Calculator

Library Link: https://pypi.org/project/cgpa-calculator/1.0.0/ 

`pip install cgpa-calculator-2`

A Python-based CGPA Calculator that helps you manage your courses, calculate your CGPA based on GPAs and credits, and display detailed course-wise results. The tool is simple, efficient, and easy to use.

## Features
- Add multiple courses with GPA and credit values.
- Calculate weighted CGPA based on the entered courses and credits.
- Display detailed results for each course, including course name, GPA, and credit hours.
- Input validation for GPA (0.0–4.0) and credit values (positive numbers).

## Getting Started

### Prerequisites
- Python 3.x installed on your system.

### Installation
1. Clone this repository or download the `CGPACalculator.py` file:
   ```bash
   https://github.com/Mustakim-Taki/cgpa_calculator
   cd cgpa_calculator


Ensure Python is installed and properly configured.<br>
### Usage
1. Add Courses
Use the add_course method to add a course with:

Course Name (string)
GPA (float, 0.0–4.0)
Credit Hours (positive integer)<br>
`from cgpa_calculator import CGPACalculator`
`calculator = CGPACalculator()`
##calculator.add_course(course_name, gpa, credit) 
`calculator.add_course("CSE110", 4.0, 3)` <br>
`calculator.add_course("CSE370", 3.7, 3)` <br>
2. Calculate CGPA<br>
Call the calculate_cgpa method to compute your CGPA:<br>
`calculator.calculate_cgpa()`
3. Show Course Results
Display all added courses with their details using the show_results method:
`calculator.show_results()`

### Example Output 
```
Your CGPA is: 3.90
Course Results:
Course: CSE110 || Credit: 3 || GPA: 4.0
Course: CSE370 || Credit: 3 || GPA: 3.7
```
cgpa-calculator-2 2.0.0
A Python-based CGPA Calculator to manage courses and calculate weighted CGPA.
Requires Python: >=3.6

# CGPA Calculator

Library Link: https://pypi.org/project/cgpa-calculator/1.0.0/ 

`pip install cgpa-calculator==1.0.0`

A Python-based CGPA Calculator that helps you manage your courses, calculate your CGPA based on GPAs and credits, and display detailed course-wise results. The tool is simple, efficient, and easy to use.

## Features
- Add multiple courses with GPA and credit values.
- Calculate weighted CGPA based on the entered courses and credits.
- Display detailed results for each course, including course name, GPA, and credit hours.
- Input validation for GPA (0.0–4.0) and credit values (positive numbers).

## Getting Started

### Prerequisites
- Python 3.x installed on your system.

### Installation
1. Clone this repository or download the `CGPACalculator.py` file:
   ```bash
   git clone https://github.com/your-username/cgpa-calculator.git
   cd cgpa-calculator


Ensure Python is installed and properly configured.<br>
### Usage
1. Add Courses
Use the add_course method to add a course with:

Course Name (string)
GPA (float, 0.0–4.0)
Credit Hours (positive integer)<br>
`from cgpa_calculator import CGPACalculator`
`calculator = CGPACalculator()`

`calculator.add_course("CSE110", 4.0, 3)` <br>
`calculator.add_course("CSE370", 3.7, 3)` <br>
2. Calculate CGPA<br>
Call the calculate_cgpa method to compute your CGPA:<br>
`calculator.calculate_cgpa()`
3. Show Course Results
Display all added courses with their details using the show_results method:
`calculator.show_results()`

### Example Output 
```
Your CGPA is: 3.90
Course Results:
Course: CSE110 || Credit: 3 || GPA: 4.0
Course: CSE370 || Credit: 3 || GPA: 3.7
```