mirror of
https://github.com/amitwh/markdown-converter.git
synced 2026-08-24 07:20:16 +05:30
fix(batch): resolve pandoc path handling and include-subfolders option
- Normalize pandoc command parsing with path.basename() to support bundled binary paths - Use bundled pandoc binary in convertWithPandoc instead of relying on PATH - Forward includeSubfolders checkbox state from renderer to main process - Add pandoc availability check before batch conversion - Re-enable Start button when batch conversion completes - Clean up obsolete dist build artifact causing test snapshot warning - Bump version to 4.4.4
This commit is contained in:
@@ -5,19 +5,19 @@
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const { analyze } = require('./writing-analytics');
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function showAnalyticsModal(tabManager) {
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const existing = document.getElementById('analytics-modal');
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if (existing) existing.remove();
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const existing = document.getElementById('analytics-modal');
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if (existing) existing.remove();
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const content = tabManager.getEditorContent();
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const metrics = analyze(content);
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const content = tabManager.getEditorContent();
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const metrics = analyze(content);
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const overlay = document.createElement('div');
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overlay.id = 'analytics-modal';
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overlay.className = 'analytics-overlay';
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const overlay = document.createElement('div');
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overlay.id = 'analytics-modal';
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overlay.className = 'analytics-overlay';
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const maxCount = metrics.topWords.length > 0 ? metrics.topWords[0].count : 1;
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const maxCount = metrics.topWords.length > 0 ? metrics.topWords[0].count : 1;
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overlay.innerHTML = `
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overlay.innerHTML = `
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<div class="analytics-modal">
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<div class="analytics-header">
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<h2>Writing Analytics</h2>
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@@ -61,11 +61,15 @@ function showAnalyticsModal(tabManager) {
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<span class="analytics-label">Avg Sentence</span>
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<span class="analytics-value">${metrics.avgSentenceLength} words</span>
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</div>
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${metrics.longestSentenceLength > 0 ? `
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${
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metrics.longestSentenceLength > 0
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? `
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<div class="analytics-row analytics-longest">
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<span class="analytics-label">Longest (${metrics.longestSentenceLength} words)</span>
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<span class="analytics-value analytics-sentence-preview">${escapeHtml(metrics.longestSentence)}</span>
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</div>` : ''}
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</div>`
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: ''
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}
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</div>
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<div class="analytics-section">
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@@ -74,39 +78,45 @@ function showAnalyticsModal(tabManager) {
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<span class="analytics-label">Unique</span>
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<span class="analytics-value">${metrics.uniqueWordCount} / ${metrics.wordCount}<small>${metrics.lexicalDiversity}%</small></span>
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</div>
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${metrics.topWords.length > 0 ? `
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${
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metrics.topWords.length > 0
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? `
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<div class="word-cloud">
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${metrics.topWords.map(w => {
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${metrics.topWords
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.map((w) => {
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const scale = 13 + Math.round((w.count / maxCount) * 3);
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return `<span class="word-tag" style="font-size:${scale}px">${escapeHtml(w.word)}<small>${w.count}</small></span>`;
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}).join('')}
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</div>` : ''}
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})
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.join('')}
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</div>`
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: ''
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}
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</div>
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</div>
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</div>
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`;
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const closeBtn = overlay.querySelector('.analytics-close');
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closeBtn.addEventListener('click', () => overlay.remove());
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overlay.addEventListener('click', (e) => {
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if (e.target === overlay) overlay.remove();
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});
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const closeBtn = overlay.querySelector('.analytics-close');
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closeBtn.addEventListener('click', () => overlay.remove());
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overlay.addEventListener('click', (e) => {
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if (e.target === overlay) overlay.remove();
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});
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const escHandler = (e) => {
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if (e.key === 'Escape') {
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overlay.remove();
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document.removeEventListener('keydown', escHandler);
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}
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};
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document.addEventListener('keydown', escHandler);
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const escHandler = (e) => {
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if (e.key === 'Escape') {
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overlay.remove();
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document.removeEventListener('keydown', escHandler);
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}
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};
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document.addEventListener('keydown', escHandler);
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document.body.appendChild(overlay);
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document.body.appendChild(overlay);
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}
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function escapeHtml(str) {
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const div = document.createElement('div');
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div.textContent = str;
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return div.innerHTML;
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const div = document.createElement('div');
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div.textContent = str;
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return div.innerHTML;
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}
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module.exports = { showAnalyticsModal };
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+177
-104
@@ -4,124 +4,197 @@
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*/
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const STOP_WORDS = new Set([
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'the', 'a', 'an', 'is', 'are', 'was', 'were', 'be', 'been',
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'have', 'has', 'had', 'do', 'does', 'did', 'will', 'would',
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'could', 'should', 'to', 'of', 'in', 'for', 'on', 'with',
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'at', 'by', 'from', 'as', 'and', 'or', 'but', 'if', 'it',
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'its', 'this', 'that', 'these', 'those', 'i', 'me', 'my',
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'we', 'our', 'you', 'your', 'he', 'him', 'his', 'she', 'her',
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'they', 'them', 'their', 'not', 'no', 'so', 'than', 'too',
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'very', 'also', 'just', 'about', 'up', 'out', 'what', 'which', 'who'
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'the',
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'a',
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'an',
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'is',
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'are',
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'was',
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'were',
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'be',
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'been',
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'have',
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'has',
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'had',
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'do',
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'does',
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'did',
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'will',
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'would',
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'could',
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'should',
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'to',
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'of',
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'in',
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'for',
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'on',
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'with',
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'at',
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'by',
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'from',
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'as',
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'and',
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'or',
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'but',
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'if',
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'it',
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'its',
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'this',
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'that',
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'these',
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'those',
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'i',
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'me',
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'my',
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'we',
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'our',
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'you',
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'your',
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'he',
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'him',
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'his',
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'she',
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'her',
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'they',
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'them',
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'their',
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'not',
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'no',
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'so',
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'than',
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'too',
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'very',
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'also',
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'just',
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'about',
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'up',
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'out',
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'what',
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'which',
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'who',
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]);
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function countSyllables(word) {
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word = word.toLowerCase().replace(/(?:[^laeiouy]es|ed|[^laeiouy]e)$/, '');
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word = word.replace(/^y/, '');
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return word.match(/[aeiouy]{1,2}/gi)?.length || 1;
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word = word.toLowerCase().replace(/(?:[^laeiouy]es|ed|[^laeiouy]e)$/, '');
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word = word.replace(/^y/, '');
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return word.match(/[aeiouy]{1,2}/gi)?.length || 1;
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}
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function extractWords(text) {
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return text.match(/[a-zA-Z]+(?:['-][a-zA-Z]+)*/g) || [];
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return text.match(/[a-zA-Z]+(?:['-][a-zA-Z]+)*/g) || [];
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}
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function getReadabilityLabel(score) {
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if (score >= 90) return 'Very Easy';
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if (score >= 70) return 'Easy';
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if (score >= 50) return 'Standard';
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if (score >= 30) return 'Difficult';
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return 'Very Difficult';
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if (score >= 90) return 'Very Easy';
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if (score >= 70) return 'Easy';
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if (score >= 50) return 'Standard';
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if (score >= 30) return 'Difficult';
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return 'Very Difficult';
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}
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function analyze(text) {
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if (!text || !text.trim()) {
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return {
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wordCount: 0,
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sentenceCount: 0,
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paragraphCount: 0,
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fleschEase: 0,
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fleschGrade: 0,
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readabilityLabel: 'N/A',
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readingTime: 0,
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speakingTime: 0,
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uniqueWordCount: 0,
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lexicalDiversity: 0,
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avgSentenceLength: 0,
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longestSentence: '',
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longestSentenceLength: 0,
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topWords: []
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};
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}
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const words = extractWords(text);
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const wordCount = words.length;
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const sentences = text.split(/[.!?]+/).map(s => s.trim()).filter(Boolean);
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const sentenceCount = Math.max(sentences.length, 1);
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const paragraphs = text.split(/\n\s*\n/).map(p => p.trim()).filter(Boolean);
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const paragraphCount = Math.max(paragraphs.length, 1);
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let totalSyllables = 0;
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for (const w of words) {
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totalSyllables += countSyllables(w);
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}
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const fleschEase = Math.round((206.835 - 1.015 * (wordCount / sentenceCount) - 84.6 * (totalSyllables / wordCount)) * 10) / 10;
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const fleschGrade = Math.round((0.39 * (wordCount / sentenceCount) + 11.8 * (totalSyllables / wordCount) - 15.59) * 10) / 10;
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const readabilityLabel = getReadabilityLabel(fleschEase);
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const readingTime = Math.ceil(wordCount / 200);
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const speakingTime = Math.ceil(wordCount / 130);
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const uniqueWords = new Set(words.map(w => w.toLowerCase()));
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const uniqueWordCount = uniqueWords.size;
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const lexicalDiversity = wordCount > 0 ? Math.round((uniqueWordCount / wordCount) * 1000) / 10 : 0;
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const avgSentenceLength = Math.round((wordCount / sentenceCount) * 10) / 10;
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let longestSentence = '';
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let longestSentenceLength = 0;
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for (const s of sentences) {
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const sWords = extractWords(s);
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if (sWords.length > longestSentenceLength) {
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longestSentenceLength = sWords.length;
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longestSentence = s.trim();
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}
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}
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if (longestSentence.length > 80) {
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longestSentence = longestSentence.substring(0, 80) + '...';
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}
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const wordFreq = {};
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for (const w of words) {
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const lower = w.toLowerCase();
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if (!STOP_WORDS.has(lower) && lower.length > 1) {
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wordFreq[lower] = (wordFreq[lower] || 0) + 1;
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}
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}
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const topWords = Object.entries(wordFreq)
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.sort((a, b) => b[1] - a[1])
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.slice(0, 10)
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.map(([word, count]) => ({ word, count }));
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if (!text || !text.trim()) {
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return {
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wordCount,
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sentenceCount,
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paragraphCount,
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fleschEase,
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fleschGrade,
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readabilityLabel,
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readingTime,
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speakingTime,
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uniqueWordCount,
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lexicalDiversity,
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avgSentenceLength,
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longestSentence,
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longestSentenceLength,
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topWords
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wordCount: 0,
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sentenceCount: 0,
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paragraphCount: 0,
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fleschEase: 0,
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fleschGrade: 0,
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readabilityLabel: 'N/A',
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readingTime: 0,
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speakingTime: 0,
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uniqueWordCount: 0,
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lexicalDiversity: 0,
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avgSentenceLength: 0,
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longestSentence: '',
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longestSentenceLength: 0,
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topWords: [],
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};
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}
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const words = extractWords(text);
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const wordCount = words.length;
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const sentences = text
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.split(/[.!?]+/)
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.map((s) => s.trim())
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.filter(Boolean);
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const sentenceCount = Math.max(sentences.length, 1);
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const paragraphs = text
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.split(/\n\s*\n/)
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.map((p) => p.trim())
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.filter(Boolean);
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const paragraphCount = Math.max(paragraphs.length, 1);
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let totalSyllables = 0;
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for (const w of words) {
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totalSyllables += countSyllables(w);
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}
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const fleschEase =
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Math.round(
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(206.835 - 1.015 * (wordCount / sentenceCount) - 84.6 * (totalSyllables / wordCount)) * 10
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) / 10;
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const fleschGrade =
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Math.round(
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(0.39 * (wordCount / sentenceCount) + 11.8 * (totalSyllables / wordCount) - 15.59) * 10
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) / 10;
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const readabilityLabel = getReadabilityLabel(fleschEase);
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const readingTime = Math.ceil(wordCount / 200);
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const speakingTime = Math.ceil(wordCount / 130);
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const uniqueWords = new Set(words.map((w) => w.toLowerCase()));
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const uniqueWordCount = uniqueWords.size;
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const lexicalDiversity =
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wordCount > 0 ? Math.round((uniqueWordCount / wordCount) * 1000) / 10 : 0;
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const avgSentenceLength = Math.round((wordCount / sentenceCount) * 10) / 10;
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let longestSentence = '';
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let longestSentenceLength = 0;
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for (const s of sentences) {
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const sWords = extractWords(s);
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if (sWords.length > longestSentenceLength) {
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longestSentenceLength = sWords.length;
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longestSentence = s.trim();
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}
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}
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if (longestSentence.length > 80) {
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longestSentence = longestSentence.substring(0, 80) + '...';
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}
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const wordFreq = {};
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for (const w of words) {
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const lower = w.toLowerCase();
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if (!STOP_WORDS.has(lower) && lower.length > 1) {
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wordFreq[lower] = (wordFreq[lower] || 0) + 1;
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}
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}
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const topWords = Object.entries(wordFreq)
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.sort((a, b) => b[1] - a[1])
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.slice(0, 10)
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.map(([word, count]) => ({ word, count }));
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return {
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wordCount,
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sentenceCount,
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paragraphCount,
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fleschEase,
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fleschGrade,
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readabilityLabel,
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readingTime,
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speakingTime,
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uniqueWordCount,
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lexicalDiversity,
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avgSentenceLength,
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longestSentence,
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longestSentenceLength,
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topWords,
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};
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}
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module.exports = { analyze };
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Reference in New Issue
Block a user