There are several classes under the tree module that you might be interested in using. Before reading usage for any particular class, it’s good to get an understanding of the one you might need in these sections. If you are a user, start with reading about Classes below. If you are a developer, you might be more interested in the Abstract classes.
Classes
The set of classes below are likely what you want to import and use in Python.
ContainerFileTree
The Container File Tree will create a tree that describes one or more containers, where each node is a folder in the path. See the tutorial for a walk through and example nodes.
Container Package Trees
Container Package Trees include ContainerPipTree and ContainerAptTree
and generally describe trees where the nodes
represent packages and versions. These trees can also be mapped with one
or more containers, and are an ideal data structure to store a representation
of packages across containers. From the container Apt or Pip tree you can easily
compare containers based on packages within, or export a feature matrix
with containers (rows) by packages (columns).
CollectionTree
A container Collection Tree represents nodes as container namespaces, and each node contains a dictionary of the possible tags for the general namespace. These trees are ideal for representing relationships between large sets of containers, and can also be used to calculate comparisons via distances in the tree.
Abstract Classes
If you are a developer, you might be interested to read about the Abstract
classes that underly the different kinds of container trees. The base of all
classes is the ContainerTreeBase, and the base of packages that use Google’s
Container-Diff
ContainerTree
The ContainerTree class is a subclass of ContainerTreeBase that expects
to build a file system tree to describe one or more containers. The json input
should have a list of dictionaries, each dictionary representing a complete
filepath (e.g., /etc/ssl). The key “Name” is required in the dictionary to
identify the file. This class might be suited for you if you have a custom
ContainerTreeBase
The ContainerTreeBase class is a base class that can read in general lists,
json, http, or other input data. The function to generate the tree, _make_tree,
is not defined and must be implemented by the subclass.
If you want to create a subclass, you can define any additional parsing needed
for your input under a function called _load. It should check that self.data
is not None, and if not, expect it to be loaded json from the input.
You can continue parsing it and save again the final result to self.data.
See ContainerDiffTree for an example.
ContainerDiffTree
This is a subclass of ContainerTree, specifically with an added _load function
to additionally parse the data loaded by the base ContainerTree class to support
the data structure exported by container diff, which is a list with the expected
structure under “Analysis”. For example:
[ {
'Analysis': [
...
{'Name': '/etc/ssl/certs/93bc0acc.0', 'Size': 1204},
{'Name': '/etc/ssl/certs/9479c8c3.0', 'Size': 1017},
...],
'AnalyzeType': 'File',
'Image': '/tmp/tmp.qXbcpKCWxg/c2f46186d20ce41a1e1cad7b362ad9f6a5b679cd6535e865c4170cc93f4501a4.tar'}]
We are only interested in the list under “Analysis,” and the kind of analysis might be File, Apt, or Pip. It’s unlikely that you’ll instantiate a ContainerDiffTree, but you might instantiate a ContainerFileTree or ContainerPipTree.