Does networkx give maximum depth (or nesting depth)?

I am using networkx to build graphs for a project.For a specific plot I need max depth (or nesting depth) of each node (something like this).

For eg.

I have multiple nodes in my graph, say-

G -> d, foo, bar, tar, zar, car, char, jar, par, radar, far, ....

where d is connected with others like this,

d -> {'foo': {'bar': {'tar': 2}, 'zar': {'car': {'char': 1}, 'jar': 'par'}}, 'radar': 'far'}

I want max depth (or connectivity) of nodes.

So, in this case - d->foo->zar->car->char (5 nodes in total)

Is there any way to calculate this using networkx (I have over 1M nodes, so the data is huge!)?

I checked their manual here.

Also checked different posts online but couldn't find the information.

No, they don't.

So, I edited their github code to add this functionality.

Code:

max_d = []

#dfs_depth base Code reference networkx

def dfs_depth(G, source=None, depth_limit=None):
    if source is None:
        nodes = G
    else:
        nodes = [source]
    visited = set()
    if depth_limit is None:
        depth_limit = len(G)
    for start in nodes:
        print(start)
        if start in visited:
            continue
        max_depth = 0
        visited.add(start)
        stack = [(start, depth_limit, iter(G[start]))]
        while stack:
            parent, depth_now, children = stack[-1]
            try:
                child = next(children)
                if child not in visited:
                    yield parent, child
                    visited.add(child)
                    if depth_now > 1:
                        if((depth_limit - depth_now + 1)>max_depth):
                            max_depth = depth_limit - depth_now + 1
                        stack.append((child, depth_now - 1, iter(G[child])))
            except StopIteration:
                stack.pop()
    global max_d
    max_d.append(max_depth)

Here max_d keeps track of the maximum depth (or nesting depth). To calculate the maximum depth of each node, a loop can be used (which iterates through all the nodes).