Minor improvements from general code readthrough (#5414)

* Add deprecated directive to reversed docstring.

* Add missing dep directives to shpfiles.

* Remove defn of INF sentinel.

* typo.

* str -> comment in forloop.

* STY: appropriate casing for var name.

6 files changed, 32 insertions, 17 deletions

diff --git a/networkx/algorithms/approximation/connectivity.py b/networkx/algorithms/approximation/connectivity.py
index 2de068ea..06347514 100644
--- a/networkx/algorithms/approximation/connectivity.py
+++ b/networkx/algorithms/approximation/connectivity.py
@@ -11,8 +11,6 @@ __all__ = [
     "all_pairs_node_connectivity",
 ]
 
-INF = float("inf")
-
 
 def local_node_connectivity(G, source, target, cutoff=None):
     """Compute node connectivity between source and target.
@@ -95,7 +93,7 @@ def local_node_connectivity(G, source, target, cutoff=None):
         return K
 
     if cutoff is None:
-        cutoff = INF
+        cutoff = float("inf")
 
     exclude = set()
     for i in range(min(possible, cutoff)):
diff --git a/networkx/algorithms/approximation/kcomponents.py b/networkx/algorithms/approximation/kcomponents.py
index 518a0274..97e4e7b2 100644
--- a/networkx/algorithms/approximation/kcomponents.py
+++ b/networkx/algorithms/approximation/kcomponents.py
@@ -199,7 +199,7 @@ class _AntiGraph(nx.Graph):
     Class for complement graphs.
 
     The main goal is to be able to work with big and dense graphs with
-    a low memory foodprint.
+    a low memory footprint.
 
     In this class you add the edges that *do not exist* in the dense graph,
     the report methods of the class return the neighbors, the edges and
diff --git a/networkx/algorithms/asteroidal.py b/networkx/algorithms/asteroidal.py
index c1bc7181..8dfa9335 100644
--- a/networkx/algorithms/asteroidal.py
+++ b/networkx/algorithms/asteroidal.py
@@ -76,16 +76,15 @@ def find_asteroidal_triple(G):
         v_neighborhood = set(G[v]).union([v])
         union_of_neighborhoods = u_neighborhood.union(v_neighborhood)
         for w in V - union_of_neighborhoods:
-            """Check for each pair of vertices whether they belong to the
-            same connected component when the closed neighborhood of the
-            third is removed."""
+            # Check for each pair of vertices whether they belong to the
+            # same connected component when the closed neighborhood of the
+            # third is removed.
             if (
                 component_structure[u][v] == component_structure[u][w]
                 and component_structure[v][u] == component_structure[v][w]
                 and component_structure[w][u] == component_structure[w][v]
             ):
                 return [u, v, w]
-
     return None
 
 
diff --git a/networkx/algorithms/chordal.py b/networkx/algorithms/chordal.py
index 7c7177af..9cc12f98 100644
--- a/networkx/algorithms/chordal.py
+++ b/networkx/algorithms/chordal.py
@@ -102,7 +102,7 @@ def find_induced_nodes(G, s, t, treewidth_bound=sys.maxsize):
 
     Returns
     -------
-    Induced_nodes : Set of nodes
+    induced_nodes : Set of nodes
         The set of induced nodes in the path from s to t in G
 
     Raises
@@ -143,23 +143,23 @@ def find_induced_nodes(G, s, t, treewidth_bound=sys.maxsize):
 
     H = nx.Graph(G)
     H.add_edge(s, t)
-    Induced_nodes = set()
+    induced_nodes = set()
     triplet = _find_chordality_breaker(H, s, treewidth_bound)
     while triplet:
         (u, v, w) = triplet
-        Induced_nodes.update(triplet)
+        induced_nodes.update(triplet)
         for n in triplet:
             if n != s:
                 H.add_edge(s, n)
         triplet = _find_chordality_breaker(H, s, treewidth_bound)
-    if Induced_nodes:
+    if induced_nodes:
         # Add t and the second node in the induced path from s to t.
-        Induced_nodes.add(t)
+        induced_nodes.add(t)
         for u in G[s]:
-            if len(Induced_nodes & set(G[u])) == 2:
-                Induced_nodes.add(u)
+            if len(induced_nodes & set(G[u])) == 2:
+                induced_nodes.add(u)
                 break
-    return Induced_nodes
+    return induced_nodes
 
 
 def chordal_graph_cliques(G):
diff --git a/networkx/readwrite/nx_shp.py b/networkx/readwrite/nx_shp.py
index 74bc0595..58acc757 100644
--- a/networkx/readwrite/nx_shp.py
+++ b/networkx/readwrite/nx_shp.py
@@ -18,7 +18,14 @@ __all__ = ["read_shp", "write_shp"]
 
 
 def read_shp(path, simplify=True, geom_attrs=True, strict=True):
-    """Generates a networkx.DiGraph from shapefiles. Point geometries are
+    """Generates a networkx.DiGraph from shapefiles.
+
+    .. deprecated:: 2.6
+
+       read_shp is deprecated and will be removed in NetworkX 3.0.
+       See https://networkx.org/documentation/latest/auto_examples/index.html#geospatial.
+
+    Point geometries are
     translated into nodes, lines into edges. Coordinate tuples are used as
     keys. Attributes are preserved, line geometries are simplified into start
     and end coordinates. Accepts a single shapefile or directory of many
@@ -196,6 +203,12 @@ def edges_from_line(geom, attrs, simplify=True, geom_attrs=True):
 
 def write_shp(G, outdir):
     """Writes a networkx.DiGraph to two shapefiles, edges and nodes.
+
+    .. deprecated:: 2.6
+
+       write_shp is deprecated and will be removed in 3.0.
+       See https://networkx.org/documentation/latest/auto_examples/index.html#geospatial.
+
     Nodes and edges are expected to have a Well Known Binary (Wkb) or
     Well Known Text (Wkt) key in order to generate geometries. Also
     acceptable are nodes with a numeric tuple key (x,y).
diff --git a/networkx/utils/contextmanagers.py b/networkx/utils/contextmanagers.py
index 870fecb8..d712e346 100644
--- a/networkx/utils/contextmanagers.py
+++ b/networkx/utils/contextmanagers.py
@@ -8,6 +8,11 @@ __all__ = ["reversed"]
 def reversed(G):
     """A context manager for temporarily reversing a directed graph in place.
 
+    .. deprecated:: 2.6
+
+       This context manager is deprecated and will be removed in 3.0.
+       Use ``G.reverse(copy=False) if G.is_directed() else G`` instead.
+
     This is a no-op for undirected graphs.
 
     Parameters