我如何能看到什么是在S3桶与boto3?(例如,写一个“ls”)?
做以下事情:
import boto3
s3 = boto3.resource('s3')
my_bucket = s3.Bucket('some/path/')
返回:
s3.Bucket(name='some/path/')
我如何看到它的内容?
我如何能看到什么是在S3桶与boto3?(例如,写一个“ls”)?
做以下事情:
import boto3
s3 = boto3.resource('s3')
my_bucket = s3.Bucket('some/path/')
返回:
s3.Bucket(name='some/path/')
我如何看到它的内容?
当前回答
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()
其他回答
从lambda函数运行aws cli命令也是一个不错的选择
import subprocess
import logging
logger = logging.getLogger()
logger.setLevel(logging.INFO)
def run_command(command):
command_list = command.split(' ')
try:
logger.info("Running shell command: \"{}\"".format(command))
result = subprocess.run(command_list, stdout=subprocess.PIPE);
logger.info("Command output:\n---\n{}\n---".format(result.stdout.decode('UTF-8')))
except Exception as e:
logger.error("Exception: {}".format(e))
return False
return True
def lambda_handler(event, context):
run_command('/opt/aws s3 ls s3://bucket-name')
这是解决方案
import boto3
s3=boto3.resource('s3')
BUCKET_NAME = 'Your S3 Bucket Name'
allFiles = s3.Bucket(BUCKET_NAME).objects.all()
for file in allFiles:
print(file.key)
下面是一个简单的函数,它返回所有文件的文件名或具有特定类型的文件,如'json', 'jpg'。
def get_file_list_s3(bucket, prefix="", file_extension=None):
"""Return the list of all file paths (prefix + file name) with certain type or all
Parameters
----------
bucket: str
The name of the bucket. For example, if your bucket is "s3://my_bucket" then it should be "my_bucket"
prefix: str
The full path to the the 'folder' of the files (objects). For example, if your files are in
s3://my_bucket/recipes/deserts then it should be "recipes/deserts". Default : ""
file_extension: str
The type of the files. If you want all, just leave it None. If you only want "json" files then it
should be "json". Default: None
Return
------
file_names: list
The list of file names including the prefix
"""
import boto3
s3 = boto3.resource('s3')
my_bucket = s3.Bucket(bucket)
file_objs = my_bucket.objects.filter(Prefix=prefix).all()
file_names = [file_obj.key for file_obj in file_objs if file_extension is not None and file_obj.key.split(".")[-1] == file_extension]
return file_names
我以前是这样做的:
import boto3
s3 = boto3.resource('s3')
bucket=s3.Bucket("bucket_name")
contents = [_.key for _ in bucket.objects.all() if "subfolders/ifany/" in _.key]
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()