semvec/pypi-packages huggingface dataset:
cbe-verify 0.1.1
A simple package to verify CBE payment receipts
Requires Python: >=3.7

# CBE Payment Receipt Verifier

![Python Version](https://img.shields.io/badge/python-3.7%2B-blue)
![License](https://img.shields.io/badge/license-MIT-green)

A robust Python package for verifying Commercial Bank of Ethiopia (CBE) payment receipts by reference number and account suffix.

## Features

- **Receipt Verification**: Validate CBE payment receipts using transaction references
- **PDF Parsing**: Extract transaction details from CBE PDF receipts
- **Error Handling**: Comprehensive error handling with retry mechanism
- **Multiple Date Formats**: Supports various date formats found in receipts
- **SSL Configuration**: Configurable SSL verification for secure connections

## Installation

```bash
pip install cbe-verify

```
## Usage 

```python

from cbe_verify import CBEVerifier

verifier = CBEVerifier()
result = verifier.verify("FT12345678", "1234578")  # Reference + last 8 digits

if result["success"]:
    print(f"Verified payment of {result['amount']} ETB")
    print(f"Transaction date: {result['date']}")
else:
    print(f"Verification failed: {result['error']}")

```

```


```
## Response Format

```bash

{
    "success": True,
    "payer": "John Doe",
    "payer_account": "XXXX1234",
    "receiver": "ABC Company",
    "receiver_account": "XXXX5678",
    "amount": 1500.00,
    "date": "2023-10-15T14:30:00",
    "reference": "FT12345678"
}

```
fengfengZhaoPypiTest 0.0.1
A simple WSGI-compliant web application layer framework
Requires Python: >=3.7


> This is a test project, upload the user test package to pypi

## Project description
myWeb is an extremely simple but WSGI-compliant web application framework. myWeb uses decorators to register routes, not only supports static routes, but also supports dynamic route resolution. You can make it follow the parameters directly in the url.


## Installing
Install using pip

```bash
pip3 install -i https://test.pypi.org/simple/ JuejinPdudoProject
```

## Simple static routing case
code:
```python
from JuejinPdudoSampleWeb import myWeb

@myWeb.routes(path="/index",methods="all")
def index(r):
    return "hello world\n"

def main():
    myWeb.run("",8888)


if __name__ == '__main__':
    main()
```

tests:
```bash
pdudo$ curl -v 127.0.0.1:8888/index
*   Trying 127.0.0.1:8888...
* Connected to 127.0.0.1 (127.0.0.1) port 8888 (#0)
> GET /index HTTP/1.1
> Host: 127.0.0.1:8888
> User-Agent: curl/7.81.0
> Accept: */*
>
* Mark bundle as not supporting multiuse
* HTTP 1.0, assume close after body
< HTTP/1.0 200 OK
< Date: Sat, 06 May 2023 06:21:17 GMT
< Server: WSGIServer/0.2 CPython/3.11.0
< Content-Length: 12
<
hello world
* Closing connection 0
pdudo$
```


## Simple Dynamic Routing Case
```python
from JuejinPdudoSampleWeb import myWeb

@myWeb.routes(path="/hello/{name}",methods="all",regular=True)
def hello(r):
    name = r.regular[0]
    return "hello %s\n" % (name)


def main():
    myWeb.run("",8888)


if __name__ == '__main__':
    main()
```

tests:
```bash
pdudo$ curl -v 127.0.0.1:8888/hello/pdudo
*   Trying 127.0.0.1:8888...
* Connected to 127.0.0.1 (127.0.0.1) port 8888 (#0)
> GET /hello/pdudo HTTP/1.1
> Host: 127.0.0.1:8888
> User-Agent: curl/7.81.0
> Accept: */*
>
* Mark bundle as not supporting multiuse
* HTTP 1.0, assume close after body
< HTTP/1.0 200 OK
< Date: Sat, 06 May 2023 06:22:11 GMT
< Server: WSGIServer/0.2 CPython/3.11.0
< Content-Length: 12
<
hello pdudo
* Closing connection 0
pdudo$
```

### End
Good luck with your use.
QAppuccinoLibrary 0.1.28
Reusable Robot Framework keyword library for QAppuccino TestOps
Requires Python: >=3.8

# QAppuccinoLibrary

Reusable Robot Framework keyword library for **QAppuccino TestOps**, designed and maintained by **LPS PH ODC**.

---

## 📦 **Installation**

Install using `pip`. The library will automatically install all required Python libraries if they are not found:

```bash
pip install QAppuccinoLibrary
```

---

## ⚙️ **Requirements**

- Python 3.8 or higher must be installed manually before using this library.
- All other required libraries will be installed automatically when you install this package.

---

## 🚀 **Usage Example**

In your `.robot` test file:

```robot
*** Settings ***
Resource          ../qappuccino/qappuccino.resource

*** Test Cases ***
Sample Test
    My Custom Keyword
```

---

## 👥 **Maintainers**

Eric Zamora  
LPS PH ODC  
[eric.zamora@lpstech.com](mailto:eric.zamora@lpstech.com)

---

## ⚠️ **License Notice**

```
-------------------------------------------------------------------------------
This code is created by LPS PH ODC.
Unauthorized use, modification, distribution, or reproduction of this code
is strictly prohibited. This code shall only be used within LPS and for
its authorized purposes.
Copyright (c) 2024 LPS. All rights reserved.
-------------------------------------------------------------------------------
```
maze-game-engine 0.1
A basic engine for basic maze games.
Requires Python: >=3.10

# Maze Game Engine
This is a basic engine for maze games. Currently, it supports mazes between one and eight dimensions; a user; and exit points.

This library has also served as my first GitHub repository (in 2021) and my first PyPi package (in 2025).

## Installation and Usage
1. Install [Python 3.10 or above](https://www.python.org/downloads) alongside its pip package manager.
2. Open a terminal of your choice and install the library:
```bash
pip install maze-game-engine -U
```
3. The library can now be imported to your projects and invoked as desired:
```py
import maze_game_engine as mge
...
```
dj-static-revision 0.10
Revision info for Django static file
Requires Python: <4.0,>=3.10
Keywords: django, static, version, cache

======================
Django Static Revision
======================

.. image:: https://madewithlove.now.sh/vn?heart=true&colorA=%23ffcd00&colorB=%23da251d
.. image:: https://badgen.net/pypi/v/dj-static-revision
   :target: https://pypi.org/project/dj-static-revision


Django plugin to provide a context variable for retrieving the version of running application.

This variable is meant to change the URL of a static file, to invalidate browser cache.


Install
-------

.. code-block:: shell

    python -m pip install dj-static-revision
    # or
    uv add dj-static-revision

`Django Static Revision` only supports Python 3.10+.


Usage
-----

Add ``dj_static_revision.context_processors.static_revision`` to your ``context_processors`` list.

.. code-block:: python

    TEMPLATES = (
        {
            'NAME': 'jinja2',
            'BACKEND': 'django_jinja.backend.Jinja2',
            'OPTIONS': {
                'context_processors': (
                    # Other context processors
                    'dj_static_revision.context_processors.static_revision',
                ),

A variable ``REVISION`` will then exists in your template, you can use it to append to static file URL.

.. code-block:: jinja

    <script src="{{ static('js/app.js') }}?v={{ REVISION }}"></script>


`Django Static Revision` retrieves revision string from Git history.
If your source code is not managed by Git, the revision info will be read from a file named `.version` placed next to `manage.py` file.


Settings
--------

The revision string will be truncated to 10 characters. You can change that by add to Django settings:

.. code-block:: python

    STATIC_REVISION_STRING_LENGTH = 10

You can also change the file for `Django Static Revision` to read revision string from, by add this setting:

.. code-block:: python

    STATIC_REVISION_VERSION_FILE = '.version'

where *.version* is a text file containing any string you want.
superchat 0.10
AI-driven discussions and multi-agent debates
Requires Python: >=3.8
Keywords: ai, chat, cli, autogen, multi-agent

# superchat

AI-driven discussions and multi-agent debates. A terminal-based CLI application for communicating with multiple AI models through OpenRouter's API.

## Features

- Interactive chat with any open source AI model on OpenRouter
- Add multiple agents to a chat to start a debate between agents

## Requirements

- **Python 3.8+** - Check with `python3 --version`
- **pip** - Usually comes with Python, check with `pip --version`
- **OpenRouter API key** - Get one at https://openrouter.ai/keys

### Installing missing dependencies on macOS:
- **Python**: `brew install python` or download from python.org

## Installation

**Install superchat with one command**

```bash
pip install superchat
```

**Test that it worked**

```bash
superchat --help
```

If you see a dialog with instructions, then you're ready to use superchat

**If `superchat command isn't found`**:

Run this command to add the install location to your PATH:

```bash
echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.zshrc && source ~/.zshrc
```

## Configuration

You'll need an OpenRouter API key to use superchat. The program will guide you through this setup automatically on first run.

**Getting your API key:**

1. Go to https://openrouter.ai/keys
2. Sign up for a free account
3. Create a new API key (starts with `sk-or-`)
4. Add credits to your account at https://openrouter.ai/credits

**Setup:**

When you first run superchat, it will detect that you don't have an API key and automatically prompt you to enter it. The key will be securely saved to your `~/.env` file for future use.

**Manual Setup (Optional):**

If you prefer to set up the API key manually:

```bash
echo "OPENROUTER_API_KEY=ADD-YOUR-KEY-HERE" > ~/.env
```

## Usage

After installation, run from any terminal:

```bash
superchat
```

Or use the short alias:

```bash
sc
```

### Debate Modes

Superchat supports two different debate modes when using multiple AI models:

#### Default Mode
In default mode, all AI agents join a shared conversation immediately. Each user message triggers responses from all agents in a round-robin format.

```bash
# Start default mode with multiple models
superchat -m llama claude deepseek
```

#### Staged Mode
In staged mode, you first have individual 1:1 conversations with each agent, then transition to a team debate with shared context from all conversations.

```bash
# Start staged mode with multiple models
superchat --flow staged -m llama claude deepseek
```

**Staged Mode Commands:**
- `/promote` - Promote current agent to team debate and move to next agent

**Staged Mode Benefits:**
- Get individual perspectives before group discussion
- Agents share context from 1:1 conversations in team phase

### Debate Rounds

Control how many times each agent responds per user message in team debates:

```bash
# Set debate rounds (1-5, default: 1)
superchat -r 3 -m llama claude
```

## Updating

To update to the latest version:

```bash
pip install --upgrade superchat
```

## Roadmap

Planned features:

```
- Web search
- Image processing
- Voice mode
```