Requests是一个非常好的库。我想用它来下载大文件(>1GB)。 问题是不可能将整个文件保存在内存中;我要分大块读。这是以下代码的一个问题:
import requests
def DownloadFile(url)
local_filename = url.split('/')[-1]
r = requests.get(url)
f = open(local_filename, 'wb')
for chunk in r.iter_content(chunk_size=512 * 1024):
if chunk: # filter out keep-alive new chunks
f.write(chunk)
f.close()
return
出于某种原因，它不是这样工作的;在将响应保存到文件之前，它仍然将响应加载到内存中。
当前回答
根据上面Roman被点赞最多的评论，下面是我的实现， 包括“下载为”和“重试”机制:
def download(url: str, file_path='', attempts=2):
"""Downloads a URL content into a file (with large file support by streaming)
:param url: URL to download
:param file_path: Local file name to contain the data downloaded
:param attempts: Number of attempts
:return: New file path. Empty string if the download failed
"""
if not file_path:
file_path = os.path.realpath(os.path.basename(url))
logger.info(f'Downloading {url} content to {file_path}')
url_sections = urlparse(url)
if not url_sections.scheme:
logger.debug('The given url is missing a scheme. Adding http scheme')
url = f'http://{url}'
logger.debug(f'New url: {url}')
for attempt in range(1, attempts+1):
try:
if attempt > 1:
time.sleep(10) # 10 seconds wait time between downloads
with requests.get(url, stream=True) as response:
response.raise_for_status()
with open(file_path, 'wb') as out_file:
for chunk in response.iter_content(chunk_size=1024*1024): # 1MB chunks
out_file.write(chunk)
logger.info('Download finished successfully')
return file_path
except Exception as ex:
logger.error(f'Attempt #{attempt} failed with error: {ex}')
return ''
其他回答
下面是异步分块下载用例的另一种方法，无需将所有文件内容读入内存。 这意味着从URL读取和写入文件都是使用asyncio库实现的(aiohttp从URL读取，aiofiles写入文件)。
以下代码应该适用于Python 3.7及更高版本。 复制粘贴前只需编辑SRC_URL和DEST_FILE变量。
import aiofiles
import aiohttp
import asyncio
async def async_http_download(src_url, dest_file, chunk_size=65536):
async with aiofiles.open(dest_file, 'wb') as fd:
async with aiohttp.ClientSession() as session:
async with session.get(src_url) as resp:
async for chunk in resp.content.iter_chunked(chunk_size):
await fd.write(chunk)
SRC_URL = "/path/to/url"
DEST_FILE = "/path/to/file/on/local/machine"
asyncio.run(async_http_download(SRC_URL, DEST_FILE))
请使用python的wget模块。下面是一个片段
import wget
wget.download(url)
您的块大小可能太大了，您是否尝试过删除它-可能一次1024字节?(同时，你可以使用with来整理语法)
def DownloadFile(url):
local_filename = url.split('/')[-1]
r = requests.get(url)
with open(local_filename, 'wb') as f:
for chunk in r.iter_content(chunk_size=1024):
if chunk: # filter out keep-alive new chunks
f.write(chunk)
return
顺便提一下，您如何推断响应已加载到内存中?
听起来好像python没有将数据刷新到文件中，从其他SO问题中，您可以尝试f.flush()和os.fsync()来强制写入文件并释放内存;
with open(local_filename, 'wb') as f:
for chunk in r.iter_content(chunk_size=1024):
if chunk: # filter out keep-alive new chunks
f.write(chunk)
f.flush()
os.fsync(f.fileno())
使用以下流代码，无论下载的文件大小如何，Python内存使用都会受到限制:
def download_file(url):
local_filename = url.split('/')[-1]
# NOTE the stream=True parameter below
with requests.get(url, stream=True) as r:
r.raise_for_status()
with open(local_filename, 'wb') as f:
for chunk in r.iter_content(chunk_size=8192):
# If you have chunk encoded response uncomment if
# and set chunk_size parameter to None.
#if chunk:
f.write(chunk)
return local_filename
注意，使用iter_content返回的字节数并不完全是chunk_size;它通常是一个大得多的随机数，并且在每次迭代中都是不同的。
参见body-content-workflow和Response。Iter_content供进一步参考。
这不是OP想问的，但是…使用urllib非常容易做到这一点:
from urllib.request import urlretrieve
url = 'http://mirror.pnl.gov/releases/16.04.2/ubuntu-16.04.2-desktop-amd64.iso'
dst = 'ubuntu-16.04.2-desktop-amd64.iso'
urlretrieve(url, dst)
或者这样，如果你想把它保存到一个临时文件:
from urllib.request import urlopen
from shutil import copyfileobj
from tempfile import NamedTemporaryFile
url = 'http://mirror.pnl.gov/releases/16.04.2/ubuntu-16.04.2-desktop-amd64.iso'
with urlopen(url) as fsrc, NamedTemporaryFile(delete=False) as fdst:
copyfileobj(fsrc, fdst)
我观察了整个过程:
watch 'ps -p 18647 -o pid,ppid,pmem,rsz,vsz,comm,args; ls -al *.iso'
我看到文件在增长，但内存使用量保持在17 MB。我错过了什么吗?
