使用Python实现可恢复式多线程下载器_Python

在数字时代，大文件下载已成为日常操作。当面对数十gb的蓝光原盘或企业级数据包时，传统单线程下载工具显得力不从心。本文将手把手教你用python打造专业级下载器，实现断点续传、多线程加速、速度限制等核心功能，让终端下载体验焕然一新。

一、智能续传：从崩溃边缘抢救进度

现代下载器的核心在于"抗中断能力"。当网络波动或意外关闭导致下载失败时，传统工具会清零进度从头开始，而我们的下载器将实现智能续传：

import os
import requests
from tqdm import tqdm
 
class resumabledownloader:
    def __init__(self, url, save_path):
        self.url = url
        self.save_path = save_path
        self.file_size = self._get_file_size()
        self.downloaded = 0
 
    def _get_file_size(self):
        response = requests.head(self.url)
        return int(response.headers['content-length'])
 
    def _check_resume_point(self):
        if os.path.exists(self.save_path):
            self.downloaded = os.path.getsize(self.save_path)
            return true
        return false
 
    def download(self):
        headers = {'range': f'bytes={self.downloaded}-'}
        response = requests.get(self.url, headers=headers, stream=true)
        
        with open(self.save_path, 'ab') as f, tqdm(
            total=self.file_size,
            desc="下载进度",
            initial=self.downloaded,
            unit='b',
            unit_scale=true
        ) as bar:
            for chunk in response.iter_content(chunk_size=8192):
                if chunk:
                    f.write(chunk)
                    bar.update(len(chunk))

这段代码实现三大核心机制：

智能续传检测：通过_check_resume_point方法自动检测已下载部分
范围请求头：使用http range头精准定位续传位置
进度可视化：结合tqdm库实现动态进度条，支持中断恢复显示

二、多线程加速：榨干网络带宽

现代网络架构普遍支持http range请求，这为多线程下载创造了条件。我们采用线程池技术实现智能分块下载：

from concurrent.futures import threadpoolexecutor
 
class multithreaddownloader(resumabledownloader):
    def __init__(self, url, save_path, threads=4):
        super().__init__(url, save_path)
        self.threads = threads
        self.chunk_size = self.file_size // threads
 
    def _download_chunk(self, start, end, thread_id):
        headers = {'range': f'bytes={start}-{end}'}
        response = requests.get(self.url, headers=headers, stream=true)
        
        with open(self.save_path, 'r+b') as f:
            f.seek(start)
            f.write(response.content)
        return end - start + 1
 
    def download(self):
        if not self._check_resume_point():
            self._create_empty_file()
 
        with threadpoolexecutor(max_workers=self.threads) as executor:
            futures = []
            for i in range(self.threads):
                start = i * self.chunk_size
                end = start + self.chunk_size - 1
                if i == self.threads - 1:
                    end = self.file_size - 1
                futures.append(executor.submit(
                    self._download_chunk, start, end, i))
            
            with tqdm(total=self.file_size, desc="多线程下载") as bar:
                for future in futures:
                    bar.update(future.result())

关键优化点：

智能分块算法：根据文件大小自动计算每个线程的下载区间
随机写入优化：使用r+b模式直接定位到文件特定位置写入
进度聚合：通过线程池的future对象实现总进度统计

三、速度控制：做网络的好邻居

在共享网络环境中，我们添加了三级限速机制：

import time
 
class speedlimiter:
    def __init__(self, max_speed):
        self.max_speed = max_speed  # 单位：kb/s
        self.last_check = time.time()
        self.downloaded = 0
 
    def throttle(self, chunk_size):
        now = time.time()
        elapsed = now - self.last_check
        self.downloaded += chunk_size
        
        if elapsed > 0:
            current_speed = (self.downloaded / 1024) / elapsed
            if current_speed > self.max_speed:
                sleep_time = (self.downloaded / (self.max_speed * 1024)) - elapsed
                if sleep_time > 0:
                    time.sleep(sleep_time)
        self.last_check = time.time()
        self.downloaded = 0

限速器实现原理：

令牌桶算法：通过时间窗口计算实际下载速度
动态调节：根据当前速度与设定值的差值自动计算休眠时间
精准控制：以kb/s为单位，支持1-10240kb/s任意速度设定

四、终端交互：打造专业级体验

我们使用rich库构建了现代化的终端界面：

from rich.console import console
from rich.panel import panel
from rich.progress import (
    progress,
    textcolumn,
    barcolumn,
    downloadcolumn,
    transferspeedcolumn,
    timeremainingcolumn,
)
 
class terminalui:
    def __init__(self):
        self.console = console()
        self.progress = progress(
            textcolumn("[bold blue]{task.description}"),
            barcolumn(),
            textcolumn("{task.completed}/{task.total}"),
            downloadcolumn(),
            transferspeedcolumn(),
            timeremainingcolumn(),
        )
 
    def display_dashboard(self, downloader):
        self.console.clear()
        self.progress.start()
        task = self.progress.add_task(
            description="初始化下载...",
            total=downloader.file_size,
            start=downloader.downloaded
        )
        
        while not downloader.is_complete():
            self.progress.update(task, 
                completed=downloader.downloaded,
                description=f"下载速度: {downloader.get_speed():.2f}kb/s"
            )
            time.sleep(0.5)
            
        self.progress.stop()
        self.console.print(panel("[green]下载完成！文件保存至：[/]" + downloader.save_path))

界面特性：

动态仪表盘：实时显示下载速度、剩余时间、传输总量
智能刷新：每0.5秒自动更新状态，平衡性能与流畅度
异常处理：自动捕获网络中断等异常并显示错误面板

五、实战部署：从开发到使用

环境准备：

pip install requests tqdm rich

基础使用：

if __name__ == "__main__":
    downloader = multithreaddownloader(
        url="https://example.com/bigfile.zip",
        save_path="./downloads/bigfile.zip",
        threads=8
    )
    
    ui = terminalui()
    ui.display_dashboard(downloader)

高级配置（支持json配置文件）：

import json
 
config = {
    "max_speed": 512,  # 限制512kb/s
    "threads": 12,
    "retry_times": 3
}
 
with open("download_config.json", "w") as f:
    json.dump(config, f)