feat: Zenzic Language Server (ZLS) Foundation & Diagnostic Engine#154
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- Hardened JSON-RPC layer with TypedDict and compliant parse error handling - Implemented O(N) rule engine integration on the in-memory document state - Decoupled state patching from diagnostic emission via manual 'select' buffering - Solved architectural debt with a 300ms CPU-friendly debounce strategy - Rotated CHANGELOG into v0.20.x archive and fixed .bumpversion.toml coverage - Documented debounced emission model in architecture docs Signed-off-by: PythonWoods-Dev <gianluca.catalano@gmail.com>
Signed-off-by: PythonWoods-Dev <gianluca.catalano@gmail.com>
Signed-off-by: PythonWoods-Dev <gianluca.catalano@gmail.com>
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Objective
This PR implements Phases 1, 2, and 3 of the architecture for the Zenzic Language Server (ZLS), introducing native support for the JSON-RPC 2.0 protocol and resolving computational debt associated with keystroke-level execution overhead.
Resolves #12.
Key Changes
zenzic lspCLI command which establishes JSON-RPC 2.0 communication overstdiowithout relying on external dependencies (pygls/lsprotocol).DocumentManager(textDocumentSync = 2) which mathematically resolves the impedance mismatch between Python string indices and UTF-16 code units (safely handling Surrogate Pairs and Emojis).AdaptiveRuleEngineto thetextDocument/publishDiagnosticsnotification, mappingline/characterproperties and structuralseveritylevels.select.select(). State updates are applied instantly, but the engine defers execution until a 300ms debounce threshold of inactivity is met.TypedDictto enforce IPC schema compliance and guard against malformed payloads. Hardened memory hygiene by accurately purging AST states within thedidCloseevent handler.Documentation
docs/explanation/language-server-architecture.mddetailing the UTF-16 incremental sync math and the single-threaded Debounce strategy.README.md.