"""Basic algorithms for depth-first searching the nodes of a graph."""
import networkx as nx
from collections import defaultdict

__all__ = [
    "dfs_edges",
    "dfs_tree",
    "dfs_predecessors",
    "dfs_successors",
    "dfs_preorder_nodes",
    "dfs_postorder_nodes",
    "dfs_labeled_edges",
]


def dfs_edges(G, source=None, depth_limit=None):
    """Iterate over edges in a depth-first-search (DFS).

    Perform a depth-first-search over the nodes of G and yield
    the edges in order. This may not generate all edges in G (see edge_dfs).

    Parameters
    ----------
    G : NetworkX graph

    source : node, optional
       Specify starting node for depth-first search and return edges in
       the component reachable from source.

    depth_limit : int, optional (default=len(G))
       Specify the maximum search depth.

    Returns
    -------
    edges: generator
       A generator of edges in the depth-first-search.

    Examples
    --------
    >>> G = nx.path_graph(5)
    >>> list(nx.dfs_edges(G, source=0))
    [(0, 1), (1, 2), (2, 3), (3, 4)]
    >>> list(nx.dfs_edges(G, source=0, depth_limit=2))
    [(0, 1), (1, 2)]

    Notes
    -----
    If a source is not specified then a source is chosen arbitrarily and
    repeatedly until all components in the graph are searched.

    The implementation of this function is adapted from David Eppstein's
    depth-first search function in `PADS`_, with modifications
    to allow depth limits based on the Wikipedia article
    "`Depth-limited search`_".

    .. _PADS: http://www.ics.uci.edu/~eppstein/PADS
    .. _Depth-limited search: https://en.wikipedia.org/wiki/Depth-limited_search

    See Also
    --------
    dfs_preorder_nodes
    dfs_postorder_nodes
    dfs_labeled_edges
    edge_dfs
    bfs_edges
    """
    if source is None:
        # edges for all components
        nodes = G
    else:
        # edges for components with source
        nodes = [source]
    visited = set()
    if depth_limit is None:
        depth_limit = len(G)
    for start in nodes:
        if start in visited:
            continue
        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:
                        stack.append((child, depth_now - 1, iter(G[child])))
            except StopIteration:
                stack.pop()


def dfs_tree(G, source=None, depth_limit=None):
    """Returns oriented tree constructed from a depth-first-search from source.

    Parameters
    ----------
    G : NetworkX graph

    source : node, optional
       Specify starting node for depth-first search.

    depth_limit : int, optional (default=len(G))
       Specify the maximum search depth.

    Returns
    -------
    T : NetworkX DiGraph
       An oriented tree

    Examples
    --------
    >>> G = nx.path_graph(5)
    >>> T = nx.dfs_tree(G, source=0, depth_limit=2)
    >>> list(T.edges())
    [(0, 1), (1, 2)]
    >>> T = nx.dfs_tree(G, source=0)
    >>> list(T.edges())
    [(0, 1), (1, 2), (2, 3), (3, 4)]

    See Also
    --------
    dfs_preorder_nodes
    dfs_postorder_nodes
    dfs_labeled_edges
    edge_dfs
    bfs_tree
    """
    T = nx.DiGraph()
    if source is None:
        T.add_nodes_from(G)
    else:
        T.add_node(source)
    T.add_edges_from(dfs_edges(G, source, depth_limit))
    return T


def dfs_predecessors(G, source=None, depth_limit=None):
    """Returns dictionary of predecessors in depth-first-search from source.

    Parameters
    ----------
    G : NetworkX graph

    source : node, optional
       Specify starting node for depth-first search.

    depth_limit : int, optional (default=len(G))
       Specify the maximum search depth.

    Returns
    -------
    pred: dict
       A dictionary with nodes as keys and predecessor nodes as values.

    Examples
    --------
    >>> G = nx.path_graph(4)
    >>> nx.dfs_predecessors(G, source=0)
    {1: 0, 2: 1, 3: 2}
    >>> nx.dfs_predecessors(G, source=0, depth_limit=2)
    {1: 0, 2: 1}

    Notes
    -----
    If a source is not specified then a source is chosen arbitrarily and
    repeatedly until all components in the graph are searched.

    The implementation of this function is adapted from David Eppstein's
    depth-first search function in `PADS`_, with modifications
    to allow depth limits based on the Wikipedia article
    "`Depth-limited search`_".

    .. _PADS: http://www.ics.uci.edu/~eppstein/PADS
    .. _Depth-limited search: https://en.wikipedia.org/wiki/Depth-limited_search

    See Also
    --------
    dfs_preorder_nodes
    dfs_postorder_nodes
    dfs_labeled_edges
    edge_dfs
    bfs_tree
    """
    return {t: s for s, t in dfs_edges(G, source, depth_limit)}


def dfs_successors(G, source=None, depth_limit=None):
    """Returns dictionary of successors in depth-first-search from source.

    Parameters
    ----------
    G : NetworkX graph

    source : node, optional
       Specify starting node for depth-first search.

    depth_limit : int, optional (default=len(G))
       Specify the maximum search depth.

    Returns
    -------
    succ: dict
       A dictionary with nodes as keys and list of successor nodes as values.

    Examples
    --------
    >>> G = nx.path_graph(5)
    >>> nx.dfs_successors(G, source=0)
    {0: [1], 1: [2], 2: [3], 3: [4]}
    >>> nx.dfs_successors(G, source=0, depth_limit=2)
    {0: [1], 1: [2]}

    Notes
    -----
    If a source is not specified then a source is chosen arbitrarily and
    repeatedly until all components in the graph are searched.

    The implementation of this function is adapted from David Eppstein's
    depth-first search function in `PADS`_, with modifications
    to allow depth limits based on the Wikipedia article
    "`Depth-limited search`_".

    .. _PADS: http://www.ics.uci.edu/~eppstein/PADS
    .. _Depth-limited search: https://en.wikipedia.org/wiki/Depth-limited_search

    See Also
    --------
    dfs_preorder_nodes
    dfs_postorder_nodes
    dfs_labeled_edges
    edge_dfs
    bfs_tree
    """
    d = defaultdict(list)
    for s, t in dfs_edges(G, source=source, depth_limit=depth_limit):
        d[s].append(t)
    return dict(d)


def dfs_postorder_nodes(G, source=None, depth_limit=None):
    """Generate nodes in a depth-first-search post-ordering starting at source.

    Parameters
    ----------
    G : NetworkX graph

    source : node, optional
       Specify starting node for depth-first search.

    depth_limit : int, optional (default=len(G))
       Specify the maximum search depth.

    Returns
    -------
    nodes: generator
       A generator of nodes in a depth-first-search post-ordering.

    Examples
    --------
    >>> G = nx.path_graph(5)
    >>> list(nx.dfs_postorder_nodes(G, source=0))
    [4, 3, 2, 1, 0]
    >>> list(nx.dfs_postorder_nodes(G, source=0, depth_limit=2))
    [1, 0]

    Notes
    -----
    If a source is not specified then a source is chosen arbitrarily and
    repeatedly until all components in the graph are searched.

    The implementation of this function is adapted from David Eppstein's
    depth-first search function in `PADS`_, with modifications
    to allow depth limits based on the Wikipedia article
    "`Depth-limited search`_".

    .. _PADS: http://www.ics.uci.edu/~eppstein/PADS
    .. _Depth-limited search: https://en.wikipedia.org/wiki/Depth-limited_search

    See Also
    --------
    dfs_edges
    dfs_preorder_nodes
    dfs_labeled_edges
    edge_dfs
    bfs_tree
    """
    edges = nx.dfs_labeled_edges(G, source=source, depth_limit=depth_limit)
    return (v for u, v, d in edges if d == "reverse")


def dfs_preorder_nodes(G, source=None, depth_limit=None):
    """Generate nodes in a depth-first-search pre-ordering starting at source.

    Parameters
    ----------
    G : NetworkX graph

    source : node, optional
       Specify starting node for depth-first search and return nodes in
       the component reachable from source.

    depth_limit : int, optional (default=len(G))
       Specify the maximum search depth.

    Returns
    -------
    nodes: generator
       A generator of nodes in a depth-first-search pre-ordering.

    Examples
    --------
    >>> G = nx.path_graph(5)
    >>> list(nx.dfs_preorder_nodes(G, source=0))
    [0, 1, 2, 3, 4]
    >>> list(nx.dfs_preorder_nodes(G, source=0, depth_limit=2))
    [0, 1, 2]

    Notes
    -----
    If a source is not specified then a source is chosen arbitrarily and
    repeatedly until all components in the graph are searched.

    The implementation of this function is adapted from David Eppstein's
    depth-first search function in `PADS`_, with modifications
    to allow depth limits based on the Wikipedia article
    "`Depth-limited search`_".

    .. _PADS: http://www.ics.uci.edu/~eppstein/PADS
    .. _Depth-limited search: https://en.wikipedia.org/wiki/Depth-limited_search

    See Also
    --------
    dfs_edges
    dfs_postorder_nodes
    dfs_labeled_edges
    bfs_edges
    """
    edges = nx.dfs_labeled_edges(G, source=source, depth_limit=depth_limit)
    return (v for u, v, d in edges if d == "forward")


def dfs_labeled_edges(G, source=None, depth_limit=None):
    """Iterate over edges in a depth-first-search (DFS) labeled by type.

    Parameters
    ----------
    G : NetworkX graph

    source : node, optional
       Specify starting node for depth-first search and return edges in
       the component reachable from source.

    depth_limit : int, optional (default=len(G))
       Specify the maximum search depth.

    Returns
    -------
    edges: generator
       A generator of triples of the form (*u*, *v*, *d*), where (*u*,
       *v*) is the edge being explored in the depth-first search and *d*
       is one of the strings 'forward', 'nontree', or 'reverse'. A
       'forward' edge is one in which *u* has been visited but *v* has
       not. A 'nontree' edge is one in which both *u* and *v* have been
       visited but the edge is not in the DFS tree. A 'reverse' edge is
       on in which both *u* and *v* have been visited and the edge is in
       the DFS tree.

    Examples
    --------

    The labels reveal the complete transcript of the depth-first search
    algorithm in more detail than, for example, :func:`dfs_edges`::

        >>> from pprint import pprint
        >>>
        >>> G = nx.DiGraph([(0, 1), (1, 2), (2, 1)])
        >>> pprint(list(nx.dfs_labeled_edges(G, source=0)))
        [(0, 0, 'forward'),
         (0, 1, 'forward'),
         (1, 2, 'forward'),
         (2, 1, 'nontree'),
         (1, 2, 'reverse'),
         (0, 1, 'reverse'),
         (0, 0, 'reverse')]

    Notes
    -----
    If a source is not specified then a source is chosen arbitrarily and
    repeatedly until all components in the graph are searched.

    The implementation of this function is adapted from David Eppstein's
    depth-first search function in `PADS`_, with modifications
    to allow depth limits based on the Wikipedia article
    "`Depth-limited search`_".

    .. _PADS: http://www.ics.uci.edu/~eppstein/PADS
    .. _Depth-limited search: https://en.wikipedia.org/wiki/Depth-limited_search

    See Also
    --------
    dfs_edges
    dfs_preorder_nodes
    dfs_postorder_nodes
    """
    # Based on http://www.ics.uci.edu/~eppstein/PADS/DFS.py
    # by D. Eppstein, July 2004.
    if source is None:
        # edges for all components
        nodes = G
    else:
        # edges for components with source
        nodes = [source]
    visited = set()
    if depth_limit is None:
        depth_limit = len(G)
    for start in nodes:
        if start in visited:
            continue
        yield start, start, "forward"
        visited.add(start)
        stack = [(start, depth_limit, iter(G[start]))]
        while stack:
            parent, depth_now, children = stack[-1]
            try:
                child = next(children)
                if child in visited:
                    yield parent, child, "nontree"
                else:
                    yield parent, child, "forward"
                    visited.add(child)
                    if depth_now > 1:
                        stack.append((child, depth_now - 1, iter(G[child])))
            except StopIteration:
                stack.pop()
                if stack:
                    yield stack[-1][0], parent, "reverse"
        yield start, start, "reverse"
