semvec/pypi-packages huggingface dataset:
coderefineai 0.1.1
A package for executing code submissions.
Requires Python: >=3.6

# CodeRefineAI
Can LLM's identify and remove Software Inefficiencies?

## Overview

CodeRefineAI is a project aimed at leveraging Large Language Models (LLMs) to identify and remove software inefficiencies. The project includes a code execution framework that allows for the submission and validation of code snippets using the Judge0 API.

## Features

- **Code Execution**: Submit and execute code snippets using the Judge0 API.
- **Template-Based Execution**: Execute code using predefined templates.
- **Direct Code Execution**: Execute entire code snippets directly without templates.
- **Submission Details**: Retrieve detailed information about code submissions.

## Installation

To install the CodeRefineAI package, follow these steps:

1. Clone the repository:

    ```sh
    git clone https://github.com/yourusername/CodeRefineAI.git
    cd CodeRefineAI
    ```

2. Install the package:

    ```sh
    pip install .
    ```

## Usage

### Example: Template-Based Execution

```python
import pandas as pd
from core.executor.executor import Executor, ExecutorResponse
from core.executor.config import Settings

# Example settings
# Example settings
settings = load_settings("/path/to/your/.env")

# Create an instance of Executor
executor = Executor(settings)

# Example metadata
metadata = pd.Series({
    "question_id": 1,
    "name": "Example Question",
    "setup_code": "class TestCaseGenerator: ...",
    "entry_point": "main",
    "import_code": "import sys",
    "test_cases": [{"input": "1 2", "output": "3"}]
})

# Execute the code
response = executor.execute(
    code_template="def {entry_point}():\n    {import_code}\n    {solution_code}\n    {test_case_code}",
    solution_code="print('Hello, world!')",
    metadata=metadata
)

print(response)
```


### Example: Direct Code Execution
```python
import pandas as pd
from core.executor.executor import Executor, ExecutorResponse
from core.executor.config import Settings

# Example settings
settings = load_settings("/path/to/your/.env")

# Create an instance of Executor
executor = Executor(settings)

# Example code, test cases, and expected results
code = """
print("hello, world!")
"""
test_cases = ""
expected_results = "hello, world!"

# Execute the code
response = executor.execute_code(
    code=code,
    test_cases=test_cases,
    expected_results=expected_results
)

print(response)
```

### Configuration
The `Settings` class is used to configure the Executor. Here is an example configuration:

```python
from core.executor.config import Settings

settings = Settings(
    judge0_base_url="https://api.judge0.com",
    judge0_api_key="your_api_key",
    self_hosted=False,
    num_runs=1
)
```

## License
This project is licensed under the MIT License. See the LICENSE file for details.

## Contributing
Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

## Contact
For any questions or inquiries, please contact the very handsome harish876.
syncstate-mqtt 1.0.2
Python dictionary state sync keeper with mqtt, read-only
Requires Python: >=3.8

# Syncstate mqtt

This package is made to read from a mqtt broker and update a python dictionary accordingly

## How to use

To use syncstate you will need a MQTT broker, for the example the broker is set up on `localhost:1883`

```python
import syncstate_mqtt

synced_dict = {"value1" : 1, "value2" : 2} # the states will not be changed my syncstate


# Create a connection manager
syncstate = syncstate_mqtt.SyncstateConnectionManager("localhost", 1883)
syncstate.attach(synced_dict) # select the dictionary to attach to

# now your dictonary is synced
while True:
    print(synced_dict)
    input()
```

## LICENSE

    Syncstate - keep python dictionary syncronised over network
    Copyright (C) 2025  Goldenbeasty

    This program is free software: you can redistribute it and/or modify
    it under the terms of the GNU Affero General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.

    This program is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU Affero General Public License for more details.

    You should have received a copy of the GNU Affero General Public License
    along with this program.  If not, see <https://www.gnu.org/licenses/>.
ctscan 0.4
A python library to scan your code for vulnerabilities.
Requires Python: >=3.6

# CTScan Code Scanner

CTScan Code Scanner is a Python-based tool designed to download and execute a CLI from AWS S3, decrypt necessary credentials, and perform code scanning operations. This tool is intended to be used as a command-line utility.

## Features

- Download CLI executable from AWS S3
- Decrypt AWS credentials using AES encryption
- Perform code scanning with various configurable options
- Output results in different formats

## Installation

To install the package, use the following command:

```bash
pip install ctscan
```

## Usage

To use the ctscan Code Scanner, run the following command:

```bash
python -m ctscan --api_key YOUR_API_KEY [options]
```

### Command-Line Arguments

- `--api_key` (required): API key for authentication
- `--app_id`: Application ID
- `--app_name`: Application name
- `--branch_name`: Branch name (default: 'default')
- `--enable_color`: Enable color in report
- `--format`: Output format
- `--is_console_report`: Enable console report (default: True)
- `--is_debug`: Enable debug logs
- `--output_file`: Output file path
- `--scan_types`: Types of scans to be triggered
- `--severity`: Severity level
- `--skip_build_fail`: Skip build fail
- `--source_dir`: Source directory (default: current working directory)
- `--version`: CLI version to use
- `--hostname`: API endpoint hostname (default: `custom-endpoint.yourdomain.io`)

## Example

```bash
python -m ctscan --api_key YOUR_API_KEY --app_name MyApp --branch_name main --format json --output_file results.json
```

## License

This project is licensed under the MIT License.

## Contributing

Contributions are welcome! Please open an issue or submit a pull request on GitHub.

## Contact

For any inquiries, please contact the project maintainers.
aspm@securin.io
bigdog 0.2510.13
Test field for pre-release package evaluation
Requires Python: >=3.6

# BigDog

## Introduction

This is a Python package currently under testing, temporarily named "bigdog". It includes ValueU and QuantityU, which are designed to handle numerical values with asymmetric uncertainty and physical units. This package provides a robust framework for managing uncertainties in scientific computations, extending traditional numerical representations with error propagation and unit management.

### Dependencies

- Python 3.6+
- `numpy`
- `scipy`
- `astropy`

### Key Features

- **ValueU**: Handles numerical values with asymmetric uncertainties.
- **QuantityU**: Extends `ValueU` by incorporating unit management using `Astropy`.
- Supports arithmetic operations with proper uncertainty propagation.
- Provides various comparison and formatting methods.
- Includes built-in documentation accessible via `.help()`.

## Installation

Currently, the package is in the alpha stage and requires manual installation. The package name "bigdog" is a temporary designation, and the latest version is **0.2510.13**.

### Installing the Package

To install the package, run the following command in your terminal:

```sh
pip install bigdog
```

### Importing and Using the Package

Once installed, you can import the necessary modules in your Python script or interactive console:

```python
from bigdog import ValueU, QuantityU
```

## Usage

### Accessing Documentation

To view detailed usage instructions for `ValueU` and `QuantityU`, use the built-in help function:

```python
ValueU().help()  # Displays detailed information on ValueU
QuantityU().help()  # Displays detailed information on QuantityU
```

These commands provide comprehensive details about object creation, mathematical operations, unit conversions, comparisons, and additional functionalities.

## License & Disclaimer

- Unauthorized modification and redistribution of the source code are strictly prohibited.
- The authors bear no responsibility for any errors, malfunctions, or unintended consequences resulting from code modifications.
- This package assumes all variables are independent (zero covariance). Users should exercise caution when working with correlated data.
## Credits

**Main Developer**: DH.Koh ([donghyeok.koh.code@gmail.com](mailto\:donghyeok.koh.code@gmail.com))\
**Collaborating Developers**: JH.Kim, KM.Heo\
**Alpha Testers**: None

## Changelog

### v0.2510.13 (2025-03-06)

- Fixed operation method priority bug.
- Improved help message formatting.
- Minor path-related fixes.

## Contact & Contributions

Bug reports and contributions are welcome! Please contact the main developer for more information.