Alex
caf8a03553
- Implemented `upsert-allewis-from-5001.js` to fetch and update Allewis data from API. - Created `upsert-missing-movement-from-5001.js` to fill missing movement and wounds data from API. - Developed `upsert-missing-movement-from-pdfs.js` to extract movement and wounds from PDF text. - Added `upsert-missing-profiles-from-pdfs.js` to fill missing profiles from PDF data. - Introduced `upsert-missing-wounds-from-pdfs.js` to update wounds data from PDF sources. - Created `validate-bestiary.js` to validate the structure of the bestiary JSON. - Updated `BestiaryTab.jsx` component to display bestiary data with improved structure and search functionality. - Added tests for `BestiaryTab` to ensure proper rendering and functionality.
60 lines
2.3 KiB
JavaScript
60 lines
2.3 KiB
JavaScript
const fs = require('fs');
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const path = require('path');
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const dataPath = path.resolve(__dirname, '../database/alexei-pdfjs.json');
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if (!fs.existsSync(dataPath)) { console.error('missing file:', dataPath); process.exit(2); }
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const j = JSON.parse(fs.readFileSync(dataPath,'utf8'));
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const findings = j.findings || [];
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function scoreFinding(f){
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const s = f.text.toLowerCase();
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let score = 0;
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if (s.includes('alexei')) score += 5;
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if (s.includes('drahj')) score += 5;
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if (/movement:\s*\d/.test(s)) score += 4;
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if (/wounds:\s*\d/.test(s)) score += 4;
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if (/profile\s*wS/i.test(s)) score += 3;
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if (/wS\s+BS\s+S\s+T\s+Ag\s+Int/i.test(s)) score += 2;
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if (/\bskills:\b/.test(s)) score += 1;
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if (/\bweapons:\b/.test(s)) score += 1;
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return score;
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}
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function findBest(){
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let best = null;
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for (const f of findings){
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const sc = scoreFinding(f);
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f._score = sc;
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if (!best || sc > best._score) best = f;
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}
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return best;
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}
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function extractFromText(text){
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const out = {};
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const m = text.match(/Movement:\s*([0-9\/]+(?:\/[0-9]+)*)/i);
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out.movement = m ? m[1].trim() : null;
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const w = text.match(/Wounds:\s*(\d{1,3})/i);
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out.wounds = w ? parseInt(w[1],10) : null;
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// profile: try label 'Profile' line, or a row of numbers after 'Profile' or after name
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const profLabel = text.match(/Profile[^\n]*\n?([\s\S]{0,200})/i);
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if (profLabel && profLabel[1]){
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const nums = profLabel[1].replace(/[()]/g,'').match(/(\d{1,2})(?:[^\d]+(\d{1,2})){8}/);
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if (nums){
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// fallback, simpler: find first 9 numbers in nearby text
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}
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}
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// simpler: find first sequence of 9 numbers in the snippet
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const seq = text.match(/(\d{1,2})(?:\s+\(?\d{1,2}\)?){8}/);
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if (seq){
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const nums = seq[0].replace(/[()]/g,'').trim().split(/\s+/).map(n=>parseInt(n,10));
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if (nums.length===9){
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const keys = ['ws','bs','s','t','ag','int','per','wp','fel'];
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out.profile = {};
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keys.forEach((k,i)=>out.profile[k]=nums[i]);
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}
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} else out.profile = null;
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return out;
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}
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const best = findBest();
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if (!best){ console.error('no candidate'); process.exit(1); }
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const extracted = extractFromText(best.text);
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const result = { pdf: best.pdf || 'unknown', page: best.page, score: best._score, extracted, snippet: best.text.slice(0,1000).replace(/\n+/g,' ') };
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console.log(JSON.stringify(result, null, 2));
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