One of the most important abstractions introduced in Jaseci is that of the walker. The semantics of this abstraction is unlike any that has existed in any programming language before.
In a nutshell, a walker is a unit of execution that retains state (its local scope) as it travels
over a graphs. Walkers walk from node to node in the graph and executing its body.
The walker’s body is specified with an opening and closing braces (
} ) and is executed to
completion on each node it lands on. In this sense a walker iterates while spooling through a
sequence of nodes that it ‘takes’ using the take keyword. We call each of these iterations
Variables declared in a walker’s body takes two forms: its context variables, those that retain state as it travels from node to node in a graph, and its local variables, those that are reinitialized for each node-bound iterations.
Walkers present a new way of thinking about programmatic execution distinct from the near-ubiquitous function based asbtraction in other languages. Instead of a functions scope being temporally pushed onto an ever increasing stack as functions call other functions. Scopes can be spacially laid out on a graph and walkers can hop around the graph taking its scope with it. A key difference in this model is in its introduction of data spacial problem solving. In the former function-based model scopes become unaccessible upon the sub-call of a function until that function returns. In contrast, walkers can access any scope at any time in a modular way.
When solving problems with walkers, a developer can think of that walker as a little self- contained robot or agent that can retain context as it spacially moves about a graph, interacting with the context in nodes and edges of that graph.
In addition to the introduction of the
take command to support new types of control flow for node-bound iterations. The keywords and semantics of
ignore are also introduced. These instruct walkers to stop walking the graph, skip over a node for execution, and ignore certain paths of the graph.