semvec/pypi-packages huggingface dataset:
stx-security-filter 0.1.2
Simple Python utility to detect malicious GET input
Requires Python: >=3.6

# stx_security_filter

**stx_security_filter** is a lightweight and easy-to-use Python library that detects malicious input patterns such as SQL Injection, XSS, and other attack vectors. It's ideal for validating GET/POST parameters in Django, Flask, FastAPI, or any Python-based web application.

---

## 🚀 Features

- Detects common SQL injection attempts
- Flags potential XSS and JavaScript payloads
- Blocks path traversal and encoded exploits
- Can be integrated directly into views, forms, or APIs
- Lightweight and dependency-free

---

## 📦 Installation

```bash
pip install -e .


Usage

from stx_security_filter import is_safe_input

user_input = request.GET.get("search")

if not is_safe_input(user_input):
    return HttpResponseForbidden("Malicious input detected.")
vpr-parser 0.1.0
Pydantic-based VOCALOID5 Editor Project (.vpr) file parser & unparser
Requires Python: >=3.11

# VPR Parser
Pydantic-based VOCALOID5 Editor Project (.vpr) file parser &amp; unparser

For parsing and manipulating Yamaha VPR (Vocaloid 5 Project) files, this tool allows you to read, modify, and save VPR files programmatically using Pydantic models for type safety and validation.

## Features

- Parsing: Extract structured data from `.vpr` files into Pydantic models.
- Modifying: Update or manipulate the parsed data and save it back to a `.vpr` file.
- Well-typed: Uses Pydantic for robust data validation and serialization.
- Detailed performance logging: Includes a `Timer` utility for profiling operations.

## Installation

Install the package using `pip`:

```bash
pip install vpr-parser
```

Or install from source:

```bash
git clone https://github.com/0x24a/vpr-parser.git
cd vpr-parser
pip install .
```

## Usage

### Parsing a VPR File

```python
from vpr_parser import VPRParser

parser = VPRParser()
vpr_file = parser.parse("path/to/your/project.vpr")

# Access parsed data
print(vpr_file.title)  # Print the project title
print(vpr_file.tracks)  # List all tracks
```

### Modifying and Saving a VPR File

```python
from vpr_parser import VPRParser, models

parser = VPRParser()
vpr_file = parser.parse("path/to/your/project.vpr")

# Modify the title
vpr_file.title = "New Project Title"

# Save the modified file
parser.dump(vpr_file, "path/to/modified_project.vpr")
```

### Available Models

The following Pydantic models are provided for working with VPR data:

- `VPRFile`: Root model representing the entire VPR file.
- `Track`: Represents a track in the project.
- `Part`: Represents a part (segment) within a track.
- `Note`: Represents a note.
- And many, literally, MANY more (see `models.py` for details).

## Development

### Dependencies

- Python 3.8+ (ONLY tested on Python 3.11+, but should work on other versions?)
- Pydantic

### Running Tests

WIP, bcs it just works...?

### Contributing

PRs are welcome! For major changes, please open an issue first to discuss the proposed changes.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
decision-engine-sdk 0.1.6
A Python SDK for interacting with the Decision Engine REST APIs
Requires Python: >=3.6

# Decision Engine SDK

This is a Python SDK for interacting with the Decision Engine REST APIs.

## Installation

```bash
pip install requests
```

## Usage

```python
import decision_engine_sdk

# Initialize the SDK
sdk = decision_engine_sdk.DecisionEngineSDK(base_url="http://localhost:8000")  # Replace with your base URL

# Decide Gateway API
payload = {"user_id": "user123", "transaction_amount": 100}
try:
    result = sdk.decide_gateway(payload)
    print(result)
except Exception as e:
    print(e)

# Update Gateway Score API
payload = {"gateway_id": "gateway1", "score": 0.8}
try:
    result = sdk.update_gateway_score(payload)
    print(result)
except Exception as e:
    print(e)