S3允许你将这些文件拆分成更小的组件。你依次上传每个组件，然后S3将它们组合成最终的对象。你可以使用FileChunkIO模块，所以如果还没有安装pip install FileChunkIO，就使用它。
更多请点击这里。

这是一个完整的文件上传脚本工作示例，使用boto 3库进行AWS S3交互，沿着filechunkio和tqdm库进行高效处理和可选的进度条显示。

from io import BytesIO
import os
import boto3
from filechunkio import FileChunkIO
from tqdm import tqdm  # Import tqdm for progress bar

# Chunk size for uploading in parts
chunk_size_bytes = 1024 * 1024 * 10 

# AWS S3 configuration
session = boto3.Session(
    aws_access_key_id='your_access_key',
    aws_secret_access_key='your_secret_key'
)
objects = session.client(service_name="s3", endpoint_url="https://your-s3-endpoint.com/", use_ssl=True)

# Local file path
source_path   = '/path/to/video.mp4'  # Full path to the local file
# Extracting the filename from the path
key_file      = os.path.basename(source_path)  # Extracted filename
# Target S3 bucket
target_bucket = "videos"  # Name of the Amazon S3 bucket
# Content type of the file
content_type  = "video/mp4"  # MIME type or content type of the file



# Create a multipart upload
response = objects.create_multipart_upload(
    ACL="public-read",
    Bucket=target_bucket,
    ContentType=content_type,
    Key=key_file
)
UploadId = response['UploadId']

# Initialize part number and parts list
part_number = 1
parts = []

try:
    # Get the total file size for tqdm
    total_size = os.path.getsize(source_path)
    # Open the local file using FileChunkIO for efficient handling of large files
    with FileChunkIO(source_path, 'rb', offset=0, closefd=True) as fd:
        for data in tqdm(iter(lambda: fd.read(chunk_size_bytes), b""), total=total_size/chunk_size_bytes, unit="MB", unit_scale=True, leave=False, dynamic_ncols=True):
            # Upload each part
            part = objects.upload_part(
                Bucket=target_bucket,
                Key=key_file,
                Body=BytesIO(data),
                PartNumber=part_number,
                UploadId=UploadId
            )
            parts.append({"PartNumber": part_number, "ETag": part["ETag"]})
            part_number += 1

    # Complete the multipart upload
    objects.complete_multipart_upload(
        Bucket=target_bucket,
        Key=key_file,
        UploadId=UploadId,
        MultipartUpload={"Parts": parts}
    )

except Exception as e:
    # Handle any exceptions, such as cleanup or logging
    print(f"Error: {e}")
    # Optionally abort the multipart upload if an error occurs
    objects.abort_multipart_upload(Bucket=target_bucket, Key=key_file, UploadId=UploadId)
    raise  # Re-raise the exception after cleanup

字符串