proxykit 0.0.1

ProxyKit is a lightweight Python package for managing and rotating proxy servers, user agents, and headers. It validates proxy lists and provides a context manager to easily inject reliable, random configurations into your HTTP requests.

ProxyKit

A lightweight Python package for managing and rotating proxy servers with built-in validation and caching.

Features

• 🔄 Multiple Data Formats: JSON, CSV, and IP list support
• ✅ Proxy Validation: Multi-threaded validation with configurable test sites
• 💾 Smart Caching: Persistent storage with TTL-based expiration
• 🎯 Context Manager: Easy integration with HTTP requests
• 🔀 Random Selection: Built-in proxy rotation

Installation

(not published yet)

pip install proxykit

Quick Start

from proxykit import ProxyKit, ProxyLoader
from proxykit.models import ProxyDataFormat

# clear all previous Proxies
ProxyKit.clear_all_data() # Optional only if you want to have fresh start

# Load proxies from various sources
ProxyLoader.load("proxies.json", format=ProxyDataFormat.JSON)
ProxyLoader.load("https://api.example.com/proxies", format=ProxyDataFormat.JSON)

# Use with context manager
with ProxyKit() as pk:
    proxy = pk.get_random_proxy()
    print(f"Using proxy: {proxy.host}:{proxy.port}")

Supported Formats

• ip and port are required rest all are optional
• ip can also be proper ip address with port separated by :, e.g: 127.0.0.1:8080 in this case port is ignored

JSON Format

ProxyLoader.load(
    "proxies.json",
    format=ProxyDataFormat.JSON,
    entry=["data"],  # Navigate nested JSON
    key_mapping={
        "ip": "host",
        "anonymity": "anonymityLevel"
    }
)

CSV Format

ProxyLoader.load(
    "proxies.csv",
    format=ProxyDataFormat.CSV,
    key_mapping={
        "ip": "proxy_host",
        "port": "proxy_port"
    }
)

IP List Format

# Simple text file with IP:PORT format
ProxyLoader.load("proxies.txt", format=ProxyDataFormat.IP)

API Reference

ProxyLoader

Method	Description
load(source, format, key_mapping, entry, token)	Load proxies from file or URL
custom_load(data)	Load pre-parsed ProxyServer objects

ProxyKit

Method	Description
get_random_proxy()	Get a random validated proxy
clear_cache()	Clear cached proxy data
clear_all_data()	Static method to clear all data

Key Mapping

Map your data fields to ProxyKit's expected format:
key-mapping required for only unmatched keys

key_mapping = {
    "ip": "your_host_field",
    "port": "your_port_field",
    "protocol": "your_protocol_field",
    "anonymity": "your_anonymity_field",
    "username": "your_username_field",
    "password": "your_password_field",
    "country": "your_country_field",
    "latency": "your_latency_field",
    "is_working": "your_status_field"
}

Models

ProxyServer

@dataclass
class ProxyServer:
    host: str
    port: int
    protocol: ProxyProtocol = ProxyProtocol.HTTP
    anonymity: AnonymityLevel = AnonymityLevel.UNKNOWN
    country: str | None = None
    latency: float | None = None
    username: str | None = None
    password: str | None = None
    is_working: bool = True

Enums

• ProxyProtocol: HTTP, HTTPS, SOCKS4, SOCKS5
• AnonymityLevel: ELITE, ANONYMOUS, TRANSPARENT, UNKNOWN
• ProxyDataFormat: JSON, CSV, IP, CUSTOM

Configuration

Customize validation settings in constants.py:

TEST_SITES = [
    "https://httpbin.org/ip",
    "https://icanhazip.com",
    "https://example.com"
]
THREADS = 25  # Validation concurrency

Requirements

• Python ≥ 3.9
• Dependencies: appdirs, requests, tqdm

License

MIT License - see LICENSE for details.

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Author

Suraj Airi - [e-mail]