Quick Usage Reference

GraphI is primarily meant for working directly on graph data. The primitives you need to familiarise yourself with are

  1. graphs, which are extended containers,
  2. nodes, which are arbitrary objects in a graph,
  3. edges, which are connections between objects in a graph, and
  4. edge values, which are values assigned to connections in a graph.

        }^{edge}] = \underbrace{\vphantom{\bigl[}\mathtt{3900}}_\mathtt{value}

This documentation page gives an overview of the most important aspects. The complete interface of GraphI is defined and documented by Graph.

Creating Graphs and adding Nodes

You can create graphs empty, via cloning, from nodes or with nodes, edges and values. For many use-cases, it is simplest to start with a set of nodes:

from graphi import graph

planets = graph("Earth", "Jupiter", "Mars", "Pluto")

Once you have a graph, it works similar to a set for nodes. You can simply add() and discard() nodes:


Working with Edges and Values

To really make use of a graph, you will want to add edges and give them values. Simply pick a connection from a node to a node and assign it a value:

# store the average distance between planets
planets["Earth":"Venus"] = 41400000

An edge is always of the form start:end, but values can be of arbitrary type. For example, you can easily add multiple values for a single edge using containers:

# add multiple values as an implicit tuple
planets["Earth":"Venus"] = 41400000, 258000000
# add multiple values as an explicit, mutable list
planets["Earth":"Mars"] = [78000000, 378000000]

The :-syntax of edges is not just pretty - it ensures that you never, ever accidentally mix up nodes and edges. This allows you to safely use the same graph[item] interface for nodes and edges.

If you need to define an edge outside of graph accesses, explicitly use Edge:

from graphi import Edge

if Edge["Venus":"Earth"] in planets:
    print("Wait, isn't there a pattern for this?")

Graphs as Python Containers

GraphI is all about letting you handle graphs with well-known interfaces. A graph is a container indexed by either nodes or edges:

del planets["Jupiter"]

Even though it contains nodes, edges and values, it presents its nodes first - similar to keys in a dict. However, you can efficiently access its various elements via views:

print("My father only told me about %d of our planets." % len(planets))
print("But I looked up %d distances between planets:" % len(planets.edges())
for planet_a, planet_b, distances in planets.items():
    print("  %s to %s: %s" % (planet_a, planet_b, '-'.join(distances)))