aparser-async 0.0.3

Command-line tool for recursively traversing directories to print file paths and their contents.

A-Parser Async Python Library

Overview

The A-Parser Async Python Library is a powerful, modern, and feature-rich solution for interacting with the A-Parser API using Python. Designed for developers who require robust and efficient API integration, this library leverages Python's asynchronous capabilities and the Pydantic library for schema validation, ensuring performance, reliability, and ease of use.

---

Key Features

🌟 Asynchronous API

The library is fully asynchronous, built on Python's asyncio and httpx to maximize performance and responsiveness. It allows for non-blocking API requests, enabling efficient parallel task management.

📜 Pydantic-Based Validation

Every request and response is validated using Pydantic models. This ensures data integrity, provides clear error messages, and reduces the risk of bugs caused by malformed data.

💡 Simplified API Integration

With thoughtfully designed methods, the library simplifies interaction with the A-Parser API, including task management, proxy checker control, and result retrieval.

🔧 Comprehensive Functionality

The library supports a wide range of features offered by the A-Parser API:

• Add tasks to the queue
• Retrieve task states and results
• Manage and delete tasks
• Control proxy checker states
• Handle task results with ease

---

Installation

pip install aparser-async

---

Usage

Import the Library

from aparser_async import AParser, schemas, AParserError

Initialize the Client

aparser = AParser(address="http://127.0.0.1", password="your_password", port=9091)

Examples

1. Ping the API

import asyncio

async def check_api():
    response = await aparser.ping()
    print(f"Ping response: {response}")

asyncio.run(check_api())

2. Add a Task

task_data = schemas.Data(
    preset="example_preset",
    parsers=[["parser1"], ["parser2"]],
    queries="example_query"
)

async def create_task():
    task_id = await aparser.add_task(task_data)
    print(f"Task created with ID: {task_id}")

asyncio.run(create_task())

3. Get Task Status

async def get_status(task_id):
    status = await aparser.get_task_state(task_id)
    print(f"Task {task_id} Status: {status.status}")

asyncio.run(get_status(task_id=12345))

4. Wait for Task Completion

async def wait_for_task(task_id):
    try:
        await aparser.wait_for_task(task_id, delay=2, timeout=60)
        print(f"Task {task_id} completed successfully!")
    except AParserError as e:
        print(f"Task {task_id} failed: {e}")

asyncio.run(wait_for_task(task_id=12345))

---

Benefits

🚀 Performance

Asynchronous programming allows you to handle multiple tasks efficiently, saving time and system resources.

✅ Reliability

The library ensures every interaction with the A-Parser API is validated, reducing the chance of runtime errors.

🛠️ Developer-Friendly

With clear documentation, intuitive APIs, and detailed logging, this library is designed for seamless integration into your Python projects.

---

Requirements

• Python 3.8+
• A running instance of A-Parser
• httpx for HTTP requests
• pydantic for schema validation

---

Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your changes. Ensure your code adheres to PEP 8 and includes tests for new functionality.

---

License

This library is licensed under the MIT License. See the LICENSE file for more details.

---

Acknowledgements

Special thanks to the developers of:

• A-Parser
• httpx
• Pydantic

---

With A-Parser Async, managing your API tasks has never been easier or more efficient. 🎉