use*_*204 4 python parallel-processing multithreading multiprocessing
我有一个可以随时启动或停止的程序。该程序用于从网页下载数据。首先,用户将在一个.csv文件中定义一堆网页,然后保存该.csv文件,然后启动程序。该程序将读取该.csv文件并将其转换为作业列表。接下来,作业被分成 5 个独立的downloader功能,这些功能并行工作但可能需要不同的时间来下载。
在downloader(其中有 5 个)完成下载网页后,我需要它来打开.csv文件并删除链接。这样,随着时间的推移,.csv文件会越来越小。问题是有时两个download函数会尝试同时更新.csv文件,会导致程序崩溃。我该如何处理?
如果这是您昨天项目的延续,您已经在内存中拥有下载列表 - 只需在加载列表中删除条目,因为它们的进程完成下载,并且只有在您退出时才在输入文件上写下整个列表 '下载器”。没有理由不断地写下这些变化。
如果您想知道(例如从外部进程)何时下载 url,即使您的“下载器”正在运行,请在downloaded.dat每次进程返回下载成功时写一个新行。
当然,在这两种情况下,从主进程/线程中写入,这样您就不必担心互斥锁。
更新- 以下是如何使用与昨天相同的代码库使用附加文件来完成此操作:
def init_downloader(params): # our downloader initializator
downloader = Downloader(**params[0]) # instantiate our downloader
downloader.run(params[1]) # run our downloader
return params # job finished, return the same params for identification
if __name__ == "__main__": # important protection for cross-platform use
downloader_params = [ # Downloaders will be initialized using these params
{"port_number": 7751},
{"port_number": 7851},
{"port_number": 7951}
]
downloader_cycle = cycle(downloader_params) # use a cycle for round-robin distribution
with open("downloaded_links.dat", "a+") as diff_file: # open your diff file
diff_file.seek(0) # rewind the diff file to the beginning to capture all lines
diff_links = {row.strip() for row in diff_file} # load downloaded links into a set
with open("input_links.dat", "r+") as input_file: # open your input file
available_links = []
download_jobs = [] # store our downloader parameters + a link here
# read our file line by line and filter out downloaded links
for row in input_file: # loop through our file
link = row.strip() # remove the extra whitespace to get the link
if link not in diff_links: # make sure link is not already downloaded
available_links.append(row)
download_jobs.append([next(downloader_cycle), link])
input_file.seek(0) # rewind our input file
input_file.truncate() # clear out the input file
input_file.writelines(available_links) # store back the available links
diff_file.seek(0) # rewind the diff file
diff_file.truncate() # blank out the diff file now that the input is updated
# and now let's get to business...
if download_jobs:
download_pool = Pool(processes=5) # make our pool use 5 processes
# run asynchronously so we can capture results as soon as they ar available
for response in download_pool.imap_unordered(init_downloader, download_jobs):
# since it returns the same parameters, the second item is a link
# add the link to our `diff` file so it doesn't get downloaded again
diff_file.write(response[1] + "\n")
else:
print("Nothing left to download...")
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整个想法是,正如我在评论中所写的那样,在下载链接时使用文件来存储下载的链接,然后在下次运行时过滤掉下载的链接并更新输入文件。这样即使您强行杀死它,它也将始终从停止的地方恢复(部分下载除外)。
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