204 lines
6.5 KiB
Python
204 lines
6.5 KiB
Python
import os
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import requests
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from bs4 import BeautifulSoup
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from concurrent.futures import ThreadPoolExecutor
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from PIL import Image
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import io
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def get_html(url, file_name, max_retries=3):
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session = requests.Session()
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adapter = requests.adapters.HTTPAdapter(max_retries=max_retries)
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session.mount("http://", adapter)
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session.mount("https://", adapter)
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try:
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response = session.get(url)
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response.raise_for_status()
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return response.text
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except Exception as e:
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print(f"Error occurred while fetching HTML from {url}: {e}")
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raise Exception(f"{file_name}, 获取网页html失败")
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def download_image(img_url, max_retries=5):
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"""
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通过给定的图片URL下载图片内容。
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参数：
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img_url (str): 图片的URL地址。
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max_retries (int, 可选): 下载失败时的最大重试次数。默认为5次。
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返回值：
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bytes or None: 成功下载图片的二进制数据，若下载失败则返回None。
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注解：
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这个函数通过发送HTTP请求下载图片文件。它使用`requests`库来获取URL返回的响应。
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如果下载成功，函数将返回图片的二进制内容（bytes格式）。
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如果下载失败，函数将尝试最多`max_retries`次重试，直到成功或达到重试次数上限。
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在每次重试之间，函数会打印错误消息来指示重试进度。
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如果重试次数用尽后仍然无法下载图片，函数将输出失败消息并返回None。
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例子：
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```
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image_url = "https://example.com/image.jpg"
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image_data = download_image(image_url)
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if image_data:
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# 处理图片数据...
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else:
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print("无法下载图片，下载失败。")
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```
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"""
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for retry in range(max_retries):
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try:
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with requests.get(img_url, stream=True) as response:
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response.raise_for_status()
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return response.content
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except Exception as e:
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if retry < max_retries - 1:
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print(
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f"Failed to download image, retrying ({retry+1}/{max_retries})..."
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)
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else:
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print("Failed to download image after multiple retries, skipping.")
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return None
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def get_img_urls(html_content):
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soup = BeautifulSoup(html_content, "html.parser")
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img_tags = soup.find("div", class_="reading-content").find_all("img")
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img_urls = []
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for img_tag in img_tags:
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img_url = img_tag.attrs["data-src"]
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img_urls.append(img_url)
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return img_urls
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def create_img_obj_list(img_url_list, file_name):
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img_obj_list = []
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for url in img_url_list:
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obj = dict()
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obj["file_name"] = file_name
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obj["url"] = url
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obj["data"] = None
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img_obj_list.append(obj)
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return img_obj_list
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def download_images_to_img_obj(img_obj):
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url = img_obj["url"]
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data = download_image(url)
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if data is None:
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file_name = img_obj["file_name"]
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print(f"{file_name}, 下载图片失败")
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raise Exception(f"{file_name}, 下载图片失败")
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img_obj["data"] = data
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def batch_download_images_to_img_obj_list(img_obj_list):
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"""
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使用 ThreadPoolExecutor 创建线程池，对 img_obj_list 中的每个图片对象调用 set_img_obj_data 函数。
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Args:
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img_obj_list (list): 图片对象列表，每个对象包含图片的数据等信息。
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Returns:
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None
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"""
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with ThreadPoolExecutor() as executor:
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executor.map(download_images_to_img_obj, img_obj_list)
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def concatenate_images_vertically(img_obj_list):
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"""
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垂直拼接长图片
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"""
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try:
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# 计算拼接后的长图宽度和总高度
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max_width = max(
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Image.open(io.BytesIO(img_obj["data"])).width for img_obj in img_obj_list
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)
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total_height = sum(
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Image.open(io.BytesIO(img_obj["data"])).height for img_obj in img_obj_list
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)
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# 创建一张新的长图
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long_image = Image.new("RGB", (max_width, total_height), color=(255, 255, 255))
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# 依次将图片在垂直方向上拼接起来
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y_offset = 0
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for img_obj in img_obj_list:
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img = Image.open(io.BytesIO(img_obj["data"]))
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img_width, img_height = img.size
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x_offset = (max_width - img_width) // 2 # 居中拼接
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long_image.paste(img, (x_offset, y_offset))
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y_offset += img_height
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return long_image
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except Exception as e:
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file_name = img_obj_list[0]["file_name"]
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print(f"{file_name}, 拼接图片失败：{e}")
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return None
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def pre_batch_task(lines):
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"""
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每个线程的批次任务
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"""
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for line in lines:
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line = line.strip() # 去掉每行开头和结尾的空白字符
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if line:
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file_name, _, url = line.partition(" - ") # 解析出 HTML 文件名和 URL 地址
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print(f"{file_name}, 开始下载")
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html_content = get_html(url, file_name)
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img_url_list = get_img_urls(html_content)
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img_obj_list = create_img_obj_list(img_url_list, file_name)
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batch_download_images_to_img_obj_list(img_obj_list)
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long_image = concatenate_images_vertically(img_obj_list) # 垂直拼接长图片
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long_image.save(f"imgs/{file_name}.png") # 保存长图到本地
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print(f"{file_name}, 完成!!")
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def read_lines_from_file(task_file):
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"""
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从文件中读取所有行并返回一个包含行的列表。
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参数：
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file_name (str): 要读取的文件名。
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返回值：
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lines (list): 包含文件中所有行的列表。
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"""
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with open(task_file, "r", encoding="utf-8") as file:
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lines = file.readlines()
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return lines
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def process_lines_in_batches(lines, batch_size):
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"""
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将行数据按照指定的批次大小，利用线程池并行处理。
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参数：
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lines (list): 包含所有行的列表。
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batch_size (int): 每个批次处理的行数。
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"""
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# 使用 ThreadPoolExecutor 创建线程池
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with ThreadPoolExecutor() as executor:
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# 按照 batch_size 将行分批次处理
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for i in range(0, len(lines), batch_size):
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batch_lines = lines[i : i + batch_size]
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executor.submit(pre_batch_task, batch_lines)
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if __name__ == "__main__":
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task_file = "input.txt"
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batch_size = 3 # 每个线程处理的行数
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lines = read_lines_from_file(task_file)
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process_lines_in_batches(lines, batch_size)
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print("finish, 程序结束...")
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