cs-data-structures

Purpose

This skill equips the OpenClaw AI to generate, manipulate, and optimize code for core data structures, including arrays, linked lists, trees (BST, AVL, B-tree), heaps, hash tables, graphs, and tries, to solve programming tasks efficiently.

When to Use

Use this skill when implementing data storage or manipulation in code, such as sorting large datasets with arrays, searching nodes in a BST, or traversing graphs for pathfinding. Apply it in scenarios requiring efficient operations like O(1) lookups in hash tables or balanced trees for sorted data.

Key Capabilities

• Arrays: Support creation, sorting (e.g., quicksort, mergesort), and searching (e.g., binary search).

• Linked Lists: Handle singly/doubly linked lists with operations like insertion, deletion, and traversal.

• Trees: Implement BST for basic searches, AVL for self-balancing, B-tree for disk-based storage; include traversals (in-order, pre-order).

• Heaps: Manage min/max heaps for priority queues, with heapify and extract operations.

• Hash Tables: Provide hashing functions, collision resolution (chaining/open addressing), and key-value operations.

• Graphs: Support adjacency lists/matrices, BFS, DFS, shortest paths (e.g., Dijkstra), and cycle detection.

• Tries: Enable prefix-based string storage and search for autocomplete features.

Usage Patterns

To invoke this skill, prefix commands with openclaw ds <structure> <action> . Always specify the structure type and action parameters for precision. For code integration, import the generated module and call functions directly. Use in a pipeline: first generate code with a command, then test it in your environment. If using in a script, set the context with --context=project-file.py to embed the code snippet. For repeated use, save outputs to a config file like JSON: {"structure": "bst", "action": "insert", "params": {"value": 5}}.

Common Commands/API

Use the OpenClaw CLI for direct execution. Commands require authentication via the environment variable $OPENCLAW_API_KEY . Example CLI flags:

• openclaw ds array create --size=10 --init=[1,2,3,4] to generate an array initialization snippet.

• openclaw ds tree bst insert --node=5 --root=var_root to add a node to a BST (output: 2-3 lines of code).

• openclaw ds graph bfs --vertices=5 --edges='[[0,1],[1,2]]' for BFS traversal code. For API integration, send HTTP requests to endpoints like POST /api/ds/{structure} with a JSON body, e.g., {"action": "sort", "params": {"array": [4,2,1], "algorithm": "quicksort"}}. Code snippets:

Example for hash table insertion

hash_table = {} # Generated by openclaw ds hash create hash_table['key'] = 'value' # Use openclaw ds hash insert --key='key' --value='value'

Example for linked list traversal

node = head # From openclaw ds linkedlist create while node: # Traverse using openclaw ds linkedlist traverse print(node.data) node = node.next

Integration Notes

Integrate this skill into your codebase by generating snippets and importing them as modules. For authentication, set $OPENCLAW_API_KEY in your environment before running commands, e.g., export OPENCLAW_API_KEY=your_api_key. Use config files in YAML format for multi-step operations: structure: bst, actions: [insert, search]. Chain with other OpenClaw skills by piping outputs, e.g., openclaw ds graph create | openclaw cs-algorithms bfs . Ensure your project uses compatible languages like Python or C++ by specifying --lang=python .

Error Handling

Always validate inputs before commands, e.g., check if structure types are valid (use openclaw ds list to query available structures). Common errors include invalid parameters (e.g., negative array size), handled by returning error codes like 400 with messages: "Error: Array size must be positive." In code snippets, wrap operations in try-except blocks, e.g.:

try: result = bst.search(5) # From openclaw ds tree bst search except KeyError: print("Node not found")

For API calls, check HTTP status codes and parse error responses. Retry transient errors with exponential backoff if API rate-limited.

Graph Relationships

• Related to: cs-algorithms (for algorithms operating on these structures, e.g., sorting arrays or traversing graphs).

• Connected to: software-engineering (for best practices in implementing data structures in production code).

• Links to: cs-networks (for graph applications in network topology).

• Associated with: ai-tools (for embedding hints like data structure queries in AI prompts).