dbx/apps/desktop/src/lib/sqlSemanticDiagnostics.ts

140 lines
4.8 KiB
TypeScript

import type { SqlCompletionColumn, SqlCompletionTable } from "@/lib/sqlCompletion";
import { getSqlCompletionContext } from "@/lib/sqlCompletion";
import type { SqlColumnReference, SqlReferenceAnalysis, SqlTableReference, SqlTextSpan } from "@/types/database";
export interface SqlSemanticDiagnostic {
span: SqlTextSpan;
message: string;
severity: "error" | "warning";
}
export interface SqlSemanticDiagnosticSchema {
tables: SqlCompletionTable[];
columnsByTable: Map<string, SqlCompletionColumn[]>;
}
export function buildSqlSemanticDiagnostics(
analysis: SqlReferenceAnalysis,
schema: SqlSemanticDiagnosticSchema,
): SqlSemanticDiagnostic[] {
const diagnostics: SqlSemanticDiagnostic[] = [];
const tables = analysis.tables.filter((table) => table.name.trim());
const knownTables = new Map<string, SqlTableReference>();
for (const table of tables) {
knownTables.set(normalizeName(table.name), table);
if (table.alias) knownTables.set(normalizeName(table.alias), table);
if (table.schema) knownTables.set(normalizeName(`${table.schema}.${table.name}`), table);
}
for (const column of analysis.columns) {
const table = resolveColumnTable(column, tables, knownTables);
if (!table) continue;
const columns = columnsForTable(table, schema.columnsByTable);
if (!columns) continue;
const columnNames = new Set(columns.map((item) => normalizeName(item.name)));
if (columnNames.has(normalizeName(column.name))) continue;
const displayName = column.qualifier ? `${column.qualifier}.${column.name}` : column.name;
diagnostics.push({
span: column.span,
message: `Unknown column ${displayName}`,
severity: "warning",
});
}
return diagnostics;
}
export function buildSqlParserErrorDiagnostic(error: unknown, sql: string): SqlSemanticDiagnostic | null {
const message = errorMessage(error);
const location = /\bat Line:\s*(\d+),\s*Column:\s*(\d+)\b/i.exec(message);
if (!location) return null;
const startLine = Number.parseInt(location[1], 10);
const startColumn = Number.parseInt(location[2], 10);
if (!Number.isFinite(startLine) || !Number.isFinite(startColumn) || startLine < 1 || startColumn < 1) return null;
const lineText = sql.split(/\r?\n/)[startLine - 1] ?? "";
const startIndex = Math.max(startColumn - 1, 0);
const token = /^[\w$]+/.exec(lineText.slice(startIndex))?.[0];
const tokenLength = Math.max(token?.length ?? 1, 1);
return {
span: {
start_line: startLine,
start_column: startColumn,
end_line: startLine,
end_column: startColumn + tokenLength - 1,
},
message,
severity: "error",
};
}
export function areSqlSemanticDiagnosticsEqual(
left: readonly SqlSemanticDiagnostic[],
right: readonly SqlSemanticDiagnostic[],
): boolean {
if (left.length !== right.length) return false;
return left.every((item, index) => {
const other = right[index];
return (
!!other &&
item.message === other.message &&
item.severity === other.severity &&
item.span.start_line === other.span.start_line &&
item.span.start_column === other.span.start_column &&
item.span.end_line === other.span.end_line &&
item.span.end_column === other.span.end_column
);
});
}
export function shouldRunSqlSemanticDiagnostics(sql: string, cursor: number): boolean {
const context = getSqlCompletionContext(sql, cursor);
if (context.suggestTables || context.exclusiveTableSuggestions || context.exclusiveColumnSuggestions) return false;
if (context.qualifier) return false;
return true;
}
function resolveColumnTable(
column: SqlColumnReference,
tables: SqlTableReference[],
knownTables: Map<string, SqlTableReference>,
): SqlTableReference | null {
if (column.qualifier) {
return knownTables.get(normalizeName(column.qualifier)) ?? null;
}
if (tables.length !== 1) return null;
return tables[0];
}
function columnsForTable(
table: SqlTableReference,
columnsByTable: Map<string, SqlCompletionColumn[]>,
): SqlCompletionColumn[] | null {
const keys = table.schema ? [`${table.schema}.${table.name}`, table.name] : [table.name];
for (const key of keys) {
const columns = columnsByTable.get(key) ?? columnsByTable.get(normalizeName(key));
// Empty metadata usually means the upstream schema lookup was inconclusive,
// so avoid surfacing a false "unknown column" warning.
if (columns && columns.length > 0) return columns;
}
return null;
}
function normalizeName(value: string): string {
let normalized = value;
while (normalized && `"'\`[]`.includes(normalized[0])) normalized = normalized.slice(1);
while (normalized && `"'\`[]`.includes(normalized[normalized.length - 1])) normalized = normalized.slice(0, -1);
return normalized.toLowerCase();
}
function errorMessage(error: unknown): string {
if (error instanceof Error) return error.message;
return String(error);
}