所以你在boto3中要求等同于aws s3 ls。这将列出所有顶级文件夹和文件。这是我能得到的最接近的结果;它只列出所有顶级文件夹。这么简单的操作居然这么难。

import boto3

def s3_ls():
  s3 = boto3.resource('s3')
  bucket = s3.Bucket('example-bucket')
  result = bucket.meta.client.list_objects(Bucket=bucket.name,
                                           Delimiter='/')
  for o in result.get('CommonPrefixes'):
    print(o.get('Prefix'))

ObjectSummary:

有两个标识符附加到ObjectSummary:

bucket_name 关键

boto3 S3: ObjectSummary

有关AWS S3文档中的对象键的更多信息:

Object Keys: When you create an object, you specify the key name, which uniquely identifies the object in the bucket. For example, in the Amazon S3 console (see AWS Management Console), when you highlight a bucket, a list of objects in your bucket appears. These names are the object keys. The name for a key is a sequence of Unicode characters whose UTF-8 encoding is at most 1024 bytes long. The Amazon S3 data model is a flat structure: you create a bucket, and the bucket stores objects. There is no hierarchy of subbuckets or subfolders; however, you can infer logical hierarchy using key name prefixes and delimiters as the Amazon S3 console does. The Amazon S3 console supports a concept of folders. Suppose that your bucket (admin-created) has four objects with the following object keys: Development/Projects1.xls Finance/statement1.pdf Private/taxdocument.pdf s3-dg.pdf Reference: AWS S3: Object Keys

下面是一些示例代码，演示如何获取桶名和对象键。

例子:

import boto3
from pprint import pprint

def main():

    def enumerate_s3():
        s3 = boto3.resource('s3')
        for bucket in s3.buckets.all():
             print("Name: {}".format(bucket.name))
             print("Creation Date: {}".format(bucket.creation_date))
             for object in bucket.objects.all():
                 print("Object: {}".format(object))
                 print("Object bucket_name: {}".format(object.bucket_name))
                 print("Object key: {}".format(object.key))

    enumerate_s3()


if __name__ == '__main__':
    main()

import boto3
s3 = boto3.resource('s3')

## Bucket to use
my_bucket = s3.Bucket('city-bucket')

## List objects within a given prefix
for obj in my_bucket.objects.filter(Delimiter='/', Prefix='city/'):
  print obj.key

输出:

city/pune.csv
city/goa.csv

在上面的注释中对@Hephaeastus的代码进行了少许修改，编写了下面的方法来列出给定路径中的文件夹和对象(文件)。类似s3 ls命令。

from boto3 import session

def s3_ls(profile=None, bucket_name=None, folder_path=None):
    folders=[]
    files=[]
    result=dict()
    bucket_name = bucket_name
    prefix= folder_path
    session = boto3.Session(profile_name=profile)
    s3_conn   = session.client('s3')
    s3_result =  s3_conn.list_objects_v2(Bucket=bucket_name, Delimiter = "/", Prefix=prefix)
    if 'Contents' not in s3_result and 'CommonPrefixes' not in s3_result:
        return []

    if s3_result.get('CommonPrefixes'):
        for folder in s3_result['CommonPrefixes']:
            folders.append(folder.get('Prefix'))

    if s3_result.get('Contents'):
        for key in s3_result['Contents']:
            files.append(key['Key'])

    while s3_result['IsTruncated']:
        continuation_key = s3_result['NextContinuationToken']
        s3_result = s3_conn.list_objects_v2(Bucket=bucket_name, Delimiter="/", ContinuationToken=continuation_key, Prefix=prefix)
        if s3_result.get('CommonPrefixes'):
            for folder in s3_result['CommonPrefixes']:
                folders.append(folder.get('Prefix'))
        if s3_result.get('Contents'):
            for key in s3_result['Contents']:
                files.append(key['Key'])

    if folders:
        result['folders']=sorted(folders)
    if files:
        result['files']=sorted(files)
    return result

这将列出给定路径下的所有对象/文件夹。Folder_path可以默认为None, method将列出桶根目录的即时内容。

首先，创建一个s3客户端对象:

s3_client = boto3.client('s3')

接下来，创建一个变量来保存bucket名称和文件夹。注意文件夹名后面的斜杠“/”:

bucket_name = 'my-bucket'
folder = 'some-folder/'

接下来，调用s3_client。List_objects_v2获取文件夹内容对象的元数据:

response = s3_client.list_objects_v2(
  Bucket=bucket_name,
  Prefix=folder
)

最后，使用对象的元数据，您可以通过调用s3_client来获取S3对象。get_object功能:

for object_metadata in response['Contents']:
    object_key = object_metadata['Key']
    response = s3_client.get_object(
        Bucket=bucket_name,
        Key=object_key
    )
    object_body = response['Body'].read()
    print(object_body)

如你所见，字符串格式的对象内容可以通过调用response['Body'].read()来获得。

我假设您已经单独配置了身份验证。

import boto3
s3 = boto3.resource('s3')

my_bucket = s3.Bucket('bucket_name')

for file in my_bucket.objects.all():
    print(file.key)