Remove top-level docstrings

Author: Mats-SX

graphdatascience/procedure_surface/api/centrality/articlerank_endpoints.py

@@ -12,9 +12,6 @@
 
 
 class ArticleRankEndpoints(ABC):
-    """
-    Abstract base class defining the API for the ArticleRank algorithm.
-    """
 
     @abstractmethod
     def mutate(

graphdatascience/procedure_surface/api/centrality/articulationpoints_endpoints.py

@@ -10,9 +10,6 @@
 
 
 class ArticulationPointsEndpoints(ABC):
-    """
-    Abstract base class defining the API for the Articulation Points algorithm.
-    """
 
     @abstractmethod
     def mutate(

graphdatascience/procedure_surface/api/centrality/betweenness_endpoints.py

@@ -12,9 +12,6 @@
 
 
 class BetweennessEndpoints(ABC):
-    """
-    Abstract base class defining the API for the Betweenness Centrality algorithm.
-    """
 
     @abstractmethod
     def mutate(

graphdatascience/procedure_surface/api/centrality/celf_endpoints.py

@@ -12,12 +12,6 @@
 
 
 class CelfEndpoints(ABC):
-    """
-    Abstract base class defining the API for the Cost Effective Lazy Forward (CELF) algorithm.
-
-    The CELF algorithm aims to find k nodes that maximize the expected spread of influence
-    in the network.
-    """
 
     @abstractmethod
     def mutate(

graphdatascience/procedure_surface/api/centrality/closeness_endpoints.py

@@ -12,13 +12,6 @@
 
 
 class ClosenessEndpoints(ABC):
-    """
-    Abstract base class defining the API for the Closeness Centrality algorithm.
-
-    Closeness centrality measures how close a node is to all other nodes in the network.
-    It's calculated as the reciprocal of the sum of the shortest path distances from
-    the node to all other nodes in the graph.
-    """
 
     @abstractmethod
     def mutate(

graphdatascience/procedure_surface/api/centrality/closeness_harmonic_endpoints.py

@@ -12,13 +12,6 @@
 
 
 class ClosenessHarmonicEndpoints(ABC):
-    """
-    Abstract base class defining the API for the Harmonic Centrality algorithm.
-
-    Harmonic centrality is a variant of closeness centrality that uses the
-    harmonic mean of shortest path distances. It handles disconnected graphs better
-    than standard closeness centrality.
-    """
 
     @abstractmethod
     def mutate(

graphdatascience/procedure_surface/api/centrality/degree_endpoints.py

@@ -12,13 +12,6 @@
 
 
 class DegreeEndpoints(ABC):
-    """
-    Abstract base class defining the API for the Degree Centrality algorithm.
-
-    Degree centrality measures the number of incoming and outgoing relationships from a node.
-    It's one of the simplest centrality measures, where a node's importance is determined by
-    the number of direct connections it has.
-    """
 
     @abstractmethod
     def mutate(

graphdatascience/procedure_surface/api/centrality/eigenvector_endpoints.py

@@ -12,14 +12,6 @@
 
 
 class EigenvectorEndpoints(ABC):
-    """
-    Abstract base class defining the API for the Eigenvector Centrality algorithm.
-
-    Eigenvector centrality measures the influence of a node in a network based on the
-    concept that connections to high-scoring nodes contribute more to the score than
-    equal connections to low-scoring nodes. It's computed as the principal eigenvector
-    of the adjacency matrix.
-    """
 
     @abstractmethod
     def mutate(

graphdatascience/procedure_surface/api/centrality/pagerank_endpoints.py

@@ -12,9 +12,6 @@
 
 
 class PageRankEndpoints(ABC):
-    """
-    Abstract base class defining the API for the PageRank algorithm.
-    """
 
     @abstractmethod
     def mutate(