Which leads nicely to.īN4 (some docs are outdated: 4.1 gives full access, but at 16x RAM cost, 4.2 drops this to 4x, and 4.3 to 1x this cost multiplier only applies outside of BN4, within the node, you effectively have 4.3 at all times): The singularity API fills in pretty much all the gaps you need for full automation: joining/working for factions, buying TOR/programs, buying/installing augments, etc. The main thing keeping them in check is the crazy negative karma (-54k) required to use them elsewhere. but a common recommendation is to leave 1.3 for later if you're itching for something new.Īs for what "new" to try, I'd recommend, in rough order:īN2 (2.1 is fine, more is of very dubious use): Gangs are pretty strong, and not too hard to script once you understand them. let servers = įor (let newServer of ns.IMO you can't go wrong just maxing 1 before moving on. All of the curly braces can be collapsed since it's just single statements in each set of braces, but I'll leave all the braces on for readability. There's a sligntly longer version of the simple iterative solution that's easier to understand, especially if you're not super familiar with arrow functions and array prototype functions. My iterative solution is meant to be clear, didactic and easy for me to understand later. So yeah you could say I favor minimalism to readability. The recursive version prints a condensed version of what you see in scan-analyze. Of course you could keep track of the path and use iterators in the iterative version, but they don’t fit so neatly with this algorithm.Ĭalling the functions might look like this. Trees don’t have a danger of adding nodes more than once, but cyclical graphs (looping paths) do and you can also check the open list for duplicates to prevent visiting a node more than once. When new nodes are encountered they closed list is checked and any new nodes are added to the open list. The open list starts with one or more nodes and they are moved to the closed list when visited. Nodes visited (closed) and nodes not yet visited (open). function* recurse(ns, host, parent=)Īny recursive function has an iterative counterpart or a way to unroll it. Say the objects were big or expensive and you might want to stop early. Iterators are especially good when you want to operate on each output one at a time, rather than all at once. Recursion is also handy because it makes it easy to maintain the path information. With recursion you will also need the yield* operator. You can simplify return data in JavaScript using an iterator and the yield operator. Because there are nested levels of recursion, you have to aggregate the results of all the children when you return the results. They can be hard to wrap your head around, but they often produce the most compact and understandable code once you understand them. Recursive methods in programming are when a function calls itself. (Ignoring the difference between breadth-first and depth-first for now.) There are two common ways of traversing these structures recursively and iteratively. ![]() ![]() I wrote a recursive version I am quite happy with and wanted to share is and discuss how to do this in detail for newer programmers. Pathfinding algorithms must do this and you will see it in other places. In computer science it’s known as traversing an undirected graph or tree. Sooner or later you will want to scan the entire list of servers.
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