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A package for representing IBM Cloud Object Storage (COS) bucket like a file system.

Project description

IBM Cloud Object Storage Simple File System Library

Problems with ibm_boto3 library

The IBMCloud Cloud Object Service has very awful representation of objects under a bucket.

For example, if you are using ibm_boto3, you can only list all objects under a bucket so that you will probably end up with a Python List of object keys in that bucket, such as:


This is really awful when you are trying to get the "end files" (i.e. those test.txt files in above example); and it is really difficult to understand the structure of this bucket.

What this library does?

This library adds a presentation layer above boto3, which expresses the flat representation of objects in a bucket (i.e. Python list) as a tree-like data structure. As such, the bucket can be represented as a file system, with the concepts of folders/directories and files. Currently, this library is able to simulate file system commands such as "cd" and "ls". This library also provides APIs for getting files in the bucket, see the Usages in next section.

For the above bucket objects, this library will represent it as

└─ source/ 
   └─ year=2018/ 
      └─ month=08/ 
         └─ day=28/ 
            └─ test1.txt 
            └─ test.txt 
         └─ day=29/ 
            └─ test.txt 
         └─ day=30/ 
            └─ test.txt 
         └─ day=31/ 
            └─ test.txt 
   └─ year=2019/ 
      └─ month=01/ 
         └─ day=01/ 
            └─ test.txt


  • Boto3 object and Key: in boto3, an object's key is represented as string like "test-bucket/source/".
  • Path: a path in this simple FS starts with bucket name, for example a path "test-bucket/source/" represents boto3 object "source/".
  • Leaves: a leaf is a COSBucketTreeNode object whose boto3 object representation is NOT a common prefix for any other boto3 objects. For example, "source/year=2018/month=08/day=28/test1.txt" in above example is a leaf's boto3 object representation.


Project is available at Pypi:

pip install ibm-cos-simple-fs


Note, paths output from this library is ALWAYS appended by bucket name thus in the form of 'bucket_name/path/to/your/stuff.txt'. When using key names with boto3 library, you should post-process the path to ignore the "bucket_name/" part.

> from ibm_cos_fs.bucket_tree import COSBucketTree

# Given flat_object_list being the one in Problem statement, building a tree structure using:
> tree = COSBucketTree(bucket_name='test-bucket', object_list=flat_object_list) # flat_object_list should be a list of strings

# Get all leaves as a list of path strings
> leaf_paths = tree.get_leaf_paths()

# Print the tree representation of the file system structure
> tree.print() 

# To get all the children nodes of a given boto3 object key, say 'source/year=2018/month=8/'
> node = tree.get_node_from_key('source/year=2018/month=8/') # This is to simulate 'cd source/year=2018/month=8/' in a file system.
> node.children # To get the children_node as a {name: TreeNode} map
# Or
> node.list_children() # To get a list of children as string. This is to simulate 'ls source/year=2018/month=8/' in a file system.

# This library also provides APIs to get leaves under a node
# To get all the leaves under a given object key, say 'source/year=2018/month=8/day=29/'
# Firstly, find the node for this key
> node = tree.get_node_from_key('source/year=2018/month=8/day=29/') 
> node.is_dir # will show whether or not current node is a directory

# Then, get the leaves nodes from a specific node
> leaf_nodes = tree.get_leaves(node) # Note, all_leaves = tree.get_leaves() will return all leaves from root

# You can then convert them to string representation (i.e. paths) by
> [str(l) for l in leaf_nodes] # or [l.path for l in leaf_nodes]

# In addition, you can get leaves as boto3 object keys
> [l.key for l in leaf_nodes]

# To get the directory that contains all given leaves; this is reverse operation to get_leaves(common_parent_node)
> common_parent_node = tree.get_common_parent_for_leaves(leaf_nodes)


Copyright © 2019 Shengyi Pan

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