So analysieren Sie PDF-Formulare mit dem ONLYOFFICE-Makro

30 April 2025Von Ksenija

In der heutigen schnelllebigen digitalen Welt fällt es Autoren, Redakteuren und Content-Erstellern oft schwer, aussagekräftige Erkenntnisse über ihre Dokumente zu gewinnen. Das Verständnis von Kennzahlen wie Lesbarkeit, Worthäufigkeit und struktureller Ausgewogenheit kann die Dokumentqualität deutlich verbessern, doch die manuelle Analyse ist zeitaufwändig und inkonsistent. In diesem Blogbeitrag zeigen wir Ihnen, wie Sie ein leistungsstarkes ONLYOFFICE-Makro erstellen, das Ihre Dokumente automatisch analysiert und umfassende Berichte erstellt.

How to analyze PDF form documents with ONLYOFFICE macro

Erstellen des Dokumentanalyse-Makros

Wir zerlegen unser Makro in funktionale Komponenten und erklären deren Funktionsweise.

Einrichten der Hauptfunktion

Der Kern unseres Makros ist die Funktion analyzeDocument(), die den gesamten Analyseprozess orchestriert:

function analyzeDocument() {
    try {
        // Get document and all text
        var oDocument = Api.GetDocument();
        var allText = "";
        var paragraphs = oDocument.GetAllParagraphs();
        
        // Check if document is empty
        if (paragraphs.length === 0) {
            console.log("Warning: Document is empty or no paragraphs found for analysis.");
            return;
        }
        
        // Collect all text
        paragraphs.forEach(function(paragraph) {
            allText += paragraph.GetText() + " ";
        });
        
        // Perform analyses
        var stats = calculateBasicStats(allText, paragraphs);
        var advancedStats = calculateAdvancedStats(allText, stats);
        var commonWords = findCommonWords(allText, 10);
        
        // Create report
        createAndAddReport(oDocument, stats, advancedStats, commonWords);
        
        // Log success
        console.log("Success: Document analysis completed. Report added to the end of the document.");
    } catch (error) {
        console.log("Error: " + error.message);
    }
}

Diese Funktion sammelt zunächst den gesamten Text aus dem Dokument, übergibt ihn dann an spezialisierte Analysefunktionen und erstellt schließlich einen Bericht. Der Try-Catch-Block stellt sicher, dass das Makro alle Fehler ordnungsgemäß verarbeitet.

Berechnung grundlegender Statistiken

Die Funktion calculateBasicStats() verarbeitet den Text, um grundlegende Metriken zu extrahieren:

function calculateBasicStats(text, paragraphs) {
    // Word count
    var words = text.split(/\s+/).filter(function(word) { 
        return word.length > 0; 
    });
    var wordCount = words.length;
    
    // Sentence count
    var sentences = text.split(/[.!?]+/).filter(function(sentence) { 
        return sentence.trim().length > 0; 
    });
    var sentenceCount = sentences.length;
    
    // Paragraph count
    var paragraphCount = paragraphs.length;
    
    // Character count
    var charCountWithSpaces = text.length;
    var charCountWithoutSpaces = text.replace(/\s+/g, "").length;
    
    // Line count (approximate)
    var lineCount = Math.ceil(charCountWithSpaces / 70);
    
    return {
        wordCount: wordCount,
        sentenceCount: sentenceCount,
        paragraphCount: paragraphCount,
        charCountWithSpaces: charCountWithSpaces,
        charCountWithoutSpaces: charCountWithoutSpaces,
        lineCount: lineCount,
        words: words,
        sentences: sentences
    };
}

Diese Funktion zerlegt den Text in Wörter und Sätze, zählt Absätze und berechnet die Anzahl von Zeichen und Zeilen.

Erweiterte Analysen durchführen

Für tiefere Einblicke berechnet die Funktion calculateAdvancedStats() komplexere Kennzahlen:

function calculateAdvancedStats(text, basicStats) {
    // Average sentence length
    var avgWordsPerSentence = basicStats.wordCount / Math.max(1, basicStats.sentenceCount);
    
    // Average paragraph length
    var avgWordsPerParagraph = basicStats.wordCount / Math.max(1, basicStats.paragraphCount);
    
    // Average word length
    var totalWordLength = basicStats.words.reduce(function(sum, word) {
        return sum + word.length;
    }, 0);
    var avgWordLength = totalWordLength / Math.max(1, basicStats.wordCount);
    
    // Readability score (simplified Flesch-Kincaid)
    var readabilityScore = 206.835 - 1.015 * avgWordsPerSentence - 84.6 * (totalWordLength / basicStats.wordCount);
    
    // Estimated reading time
    var readingTimeMinutes = Math.ceil(basicStats.wordCount / 200);
    
    return {
        avgWordsPerSentence: avgWordsPerSentence,
        avgWordsPerParagraph: avgWordsPerParagraph,
        avgWordLength: avgWordLength,
        readabilityScore: readabilityScore,
        readingTimeMinutes: readingTimeMinutes
    };
}

Dadurch werden die durchschnittliche Satz- und Absatzlänge, die Lesbarkeitswerte und die geschätzte Lesezeit berechnet.

Analyse der Worthäufigkeit

Die Funktion findCommonWords() ermittelt die am häufigsten verwendeten Wörter:

function findCommonWords(text, limit) {
    // Clean text and convert to lowercase
    var cleanText = text.toLowerCase().replace(/[.,\/#!$%\^&\*;:{}=\-_`~()]/g, "");
    
    // Split into words
    var words = cleanText.split(/\s+/).filter(function(word) { 
        return word.length > 3; 
    });
    
    // Calculate word frequencies
    var wordFrequency = {};
    words.forEach(function(word) {
        wordFrequency[word] = (wordFrequency[word] || 0) + 1;
    });
    
    // Filter stop words
    var stopWords = ["this", "that", "with", "from", "have", "been"];
    stopWords.forEach(function(stopWord) {
        delete wordFrequency[stopWord];
    });
    
    // Sort by frequency
    var sortedWords = Object.keys(wordFrequency).sort(function(a, b) {
        return wordFrequency[b] - wordFrequency[a];
    });
    
    // Return top N words
    return sortedWords.slice(0, limit).map(function(word) {
        return { word: word, frequency: wordFrequency[word] };
    });
}
function findCommonWords(text, limit) {
    // Clean text and convert to lowercase
    var cleanText = text.toLowerCase().replace(/[.,\/#!$%\^&\*;:{}=\-_`~()]/g, "");
    
    // Split into words
    var words = cleanText.split(/\s+/).filter(function(word) { 
        return word.length > 3; 
    });
    
    // Calculate word frequencies
    var wordFrequency = {};
    words.forEach(function(word) {
        wordFrequency[word] = (wordFrequency[word] || 0) + 1;
    });
    
    // Filter stop words
    var stopWords = ["this", "that", "with", "from", "have", "been"];
    stopWords.forEach(function(stopWord) {
        delete wordFrequency[stopWord];
    });
    
    // Sort by frequency
    var sortedWords = Object.keys(wordFrequency).sort(function(a, b) {
        return wordFrequency[b] - wordFrequency[a];
    });
    
    // Return top N words
    return sortedWords.slice(0, limit).map(function(word) {
        return { word: word, frequency: wordFrequency[word] };
    });
}

Diese Funktion entfernt Satzzeichen, filtert häufige Füllwörter heraus und gibt die am häufigsten verwendeten Wörter im Dokument zurück.

Bericht erstellen

Abschließend kompiliert und formatiert die Funktion createAndAddReport() alle Analyseergebnisse:

function createAndAddReport(oDocument, basicStats, advancedStats, commonWords) {
    // Add new page
    var oParagraph = Api.CreateParagraph();
    oParagraph.AddPageBreak();
    oDocument.AddElement(oDocument.GetElementsCount(), oParagraph);
    
    // Add title
    var oHeading = Api.CreateParagraph();
    oHeading.AddText("DOCUMENT ANALYSIS REPORT");
    oDocument.AddElement(oDocument.GetElementsCount(), oHeading);
    
    // Add basic statistics section
    var oSubHeading = Api.CreateParagraph();
    oSubHeading.AddText("BASIC STATISTICS");
    oDocument.AddElement(oDocument.GetElementsCount(), oSubHeading);
    
    // Add statistics content
    // ... (code that adds individual statistics)
    
    // Add advanced analysis section
    // ... (code that adds advanced metrics)
    
    // Add word frequency section
    // ... (code that adds word frequency list)
    
    // Add footer
    var oFootnotePara = Api.CreateParagraph();
    oFootnotePara.AddText("This report was generated by OnlyOffice Document Statistics and Analysis Tool on " + 
                        new Date().toLocaleString() + ".");
    oDocument.AddElement(oDocument.GetElementsCount(), oFootnotePara);
}

Diese Funktion erstellt am Ende des Dokuments einen strukturierten Bericht mit allen Analyseergebnissen.

How to analyze PDF form documents with ONLYOFFICE macro

Vollständiger Makrocode

Hier ist der vollständige Makrocode, den Sie kopieren und verwenden können:

(function() {
    // Main function - starts all operations
    function analyzeDocument() {
        try {
            // Get document and all text
            var oDocument = Api.GetDocument();
            var allText = "";
            var paragraphs = oDocument.GetAllParagraphs();
            
            // Check if document is empty
            if (paragraphs.length === 0) {
                console.log("Warning: Document is empty or no paragraphs found for analysis.");
                return;
            }
            
            // Collect all text
            paragraphs.forEach(function(paragraph) {
                allText += paragraph.GetText() + " ";
            });
            
            // Calculate basic statistics
            var stats = calculateBasicStats(allText, paragraphs);
            
            // Perform advanced analysis
            var advancedStats = calculateAdvancedStats(allText, stats);
            
            // Find most common words
            var commonWords = findCommonWords(allText, 10);
            
            // Create and add report to the document
            createAndAddReport(oDocument, stats, advancedStats, commonWords);
            
            // Inform user
            console.log("Success: Document analysis completed. Report added to the end of the document.");
        } catch (error) {
           console.log("Error: An error occurred during processing: " +         error.message);
        }
    }
    
    // Calculate basic statistics
    function calculateBasicStats(text, paragraphs) {
        // Word count
        var words = text.split(/\s+/).filter(function(word) { 
            return word.length > 0; 
        });
        var wordCount = words.length;
        
        // Sentence count
        var sentences = text.split(/[.!?]+/).filter(function(sentence) { 
            return sentence.trim().length > 0; 
        });
 var sentenceCount = sentences.length;
        
        // Paragraph count
        var paragraphCount = paragraphs.length;
        
        // Character count (with and without spaces)
        var charCountWithSpaces = text.length;
        var charCountWithoutSpaces = text.replace(/\s+/g, "").length;
        
        // Line count (approximate)
        var lineCount = Math.ceil(charCountWithSpaces / 70); // Approximately 70 characters/line
   return {
            wordCount: wordCount,
            sentenceCount: sentenceCount,
            paragraphCount: paragraphCount,
            charCountWithSpaces: charCountWithSpaces,
            charCountWithoutSpaces: charCountWithoutSpaces,
            lineCount: lineCount,
            words: words,
            sentences: sentences
        };
    }
    
    // Calculate advanced statistics
    function calculateAdvancedStats(text, basicStats) {
        // Average sentence length (in words)
        var avgWordsPerSentence = basicStats.wordCount / Math.max(1, basicStats.sentenceCount);
        
        // Average paragraph length (in words)
        var avgWordsPerParagraph = basicStats.wordCount / Math.max(1, basicStats.paragraphCount);
        
        // Average word length (in characters)
        var totalWordLength = basicStats.words.reduce(function(sum, word) {
            return sum + word.length;
        }, 0);
        var avgWordLength = totalWordLength / Math.max(1, basicStats.wordCount);
        
        // Readability score (simplified Flesch-Kincaid)
        var readabilityScore = 206.835 - 1.015 * (basicStats.wordCount / Math.max(1, basicStats.sentenceCount)) - 84.6 * (totalWordLength / Math.max(1, basicStats.wordCount));
        
        // Estimated reading time (minutes)
        var readingTimeMinutes = Math.ceil(basicStats.wordCount / 200); // Average reading speed 200 words/minute
        
        return {
            avgWordsPerSentence: avgWordsPerSentence,
            avgWordsPerParagraph: avgWordsPerParagraph,
            avgWordLength: avgWordLength,
            readabilityScore: readabilityScore,
            readingTimeMinutes: readingTimeMinutes
        };
    }
    
    // Find most common words
    function findCommonWords(text, limit) {
        // Clean text and convert to lowercase
        var cleanText = text.toLowerCase().replace(/[.,\/#!$%\^&\*;:{}=\-_`~()]/g, "");
        
   // Split into words
        var words = cleanText.split(/\s+/).filter(function(word) { 
            return word.length > 3; // Filter out very short words
        });
   // Calculate word frequencies
        var wordFrequency = {};
        words.forEach(function(word) {
            if (wordFrequency[word]) {
                wordFrequency[word]++;
            } else {
                wordFrequency[word] = 1;
            }
        });

   // Filter stop words (common English words)
        var stopWords = ["this", "that", "these", "those", "with", "from", "have", "been", "were", "they", "their", "what", "when", "where", "which", "there", "will", "would", "could", "should", "about", "also"];
        stopWords.forEach(function(stopWord) {
            if (wordFrequency[stopWord]) {
                delete wordFrequency[stopWord];
            }
        });
        
        // Sort by frequency
        var sortedWords = Object.keys(wordFrequency).sort(function(a, b) {
            return wordFrequency[b] - wordFrequency[a];
        });
        
        // Take top N words
        var topWords = sortedWords.slice(0, limit);
        
        // Return results as word-frequency pairs
        return topWords.map(function(word) {
            return {
                word: word,
                frequency: wordFrequency[word]
            };
        });
    }
   
    // Create and add report to document
    function createAndAddReport(oDocument, basicStats, advancedStats, commonWords) {
        // Add new page
        var oParagraph = Api.CreateParagraph();
        oParagraph.AddPageBreak();
        oDocument.AddElement(oDocument.GetElementsCount(), oParagraph);
        
        // Main title - highlighting in capital letters
        var oHeading = Api.CreateParagraph();
        oHeading.AddText("DOCUMENT ANALYSIS REPORT");
        oDocument.AddElement(oDocument.GetElementsCount(), oHeading);
        
        // Subheading - in capital letters
        var oSubHeading = Api.CreateParagraph();
        oSubHeading.AddText("BASIC STATISTICS");
        oDocument.AddElement(oDocument.GetElementsCount(), oSubHeading);

        // Add basic statistics
        var oStatsPara = Api.CreateParagraph();
        oStatsPara.AddText("• Word Count: " + basicStats.wordCount);
        oDocument.AddElement(oDocument.GetElementsCount(), oStatsPara);
        
        oStatsPara = Api.CreateParagraph();
        oStatsPara.AddText("• Sentence Count: " + basicStats.sentenceCount);
        oDocument.AddElement(oDocument.GetElementsCount(), oStatsPara);
        
        oStatsPara = Api.CreateParagraph();
        oStatsPara.AddText("• Paragraph Count: " +      basicStats.paragraphCount);
        oDocument.AddElement(oDocument.GetElementsCount(), oStatsPara);
        
        oStatsPara = Api.CreateParagraph();
        oStatsPara.AddText("• Character Count (with spaces): " +  basicStats.charCountWithSpaces);
        oDocument.AddElement(oDocument.GetElementsCount(), oStatsPara);
        
        oStatsPara = Api.CreateParagraph();
        oStatsPara.AddText("• Character Count (without spaces): " +  basicStats.charCountWithoutSpaces);
        oDocument.AddElement(oDocument.GetElementsCount(), oStatsPara);
        

        oStatsPara = Api.CreateParagraph();
        oStatsPara.AddText("• Estimated Line Count: " + basicStats.lineCount);
        oDocument.AddElement(oDocument.GetElementsCount(), oStatsPara);
        
        // Advanced analysis title
        oSubHeading = Api.CreateParagraph();
        oSubHeading.AddText("ADVANCED ANALYSIS");
        oDocument.AddElement(oDocument.GetElementsCount(), oSubHeading);
        
        // Add advanced analysis results
        oStatsPara = Api.CreateParagraph();
        oStatsPara.AddText("• Average Sentence Length: " + advancedStats.avgWordsPerSentence.toFixed(2) + " words");
        oDocument.AddElement(oDocument.GetElementsCount(), oStatsPara);
        
        oStatsPara = Api.CreateParagraph();
        oStatsPara.AddText("• Average Paragraph Length: " + advancedStats.avgWordsPerParagraph.toFixed(2) + " words");
        oDocument.AddElement(oDocument.GetElementsCount(), oStatsPara);
        
        oStatsPara = Api.CreateParagraph();
        oStatsPara.AddText("• Average Word Length: " + advancedStats.avgWordLength.toFixed(2) + " characters");
        oDocument.AddElement(oDocument.GetElementsCount(), oStatsPara);
        
        oStatsPara = Api.CreateParagraph();
        oStatsPara.AddText("• Readability Score: " + advancedStats.readabilityScore.toFixed(2));
        oDocument.AddElement(oDocument.GetElementsCount(), oStatsPara);
        
        oStatsPara = Api.CreateParagraph();
        oStatsPara.AddText("• Estimated Reading Time: " + advancedStats.readingTimeMinutes + " minutes");
        oDocument.AddElement(oDocument.GetElementsCount(), oStatsPara);
        
        // Common words title
        oSubHeading = Api.CreateParagraph();
        oSubHeading.AddText("MOST FREQUENTLY USED WORDS");
        oDocument.AddElement(oDocument.GetElementsCount(), oSubHeading);
        
        // We'll create a simple list instead of a table
        if (commonWords.length > 0) {
            for (var i = 0; i < commonWords.length; i++) {
                var oWordPara = Api.CreateParagraph();
                oWordPara.AddText((i + 1) + ". " + commonWords[i].word + " (" + commonWords[i].frequency + " times)");
                oDocument.AddElement(oDocument.GetElementsCount(), oWordPara);
            }
        } else {
            var oNoneFoundPara = Api.CreateParagraph();
            oNoneFoundPara.AddText("No frequently used words found.");
            oDocument.AddElement(oDocument.GetElementsCount(), oNoneFoundPara);
        }
        
        // Footer note
        var oFootnotePara = Api.CreateParagraph();
        oFootnotePara.AddText("This report was generated by OnlyOffice Document Statistics and Analysis Tool on " + 
                            new Date().toLocaleString() + ".");
        oDocument.AddElement(oDocument.GetElementsCount(), oFootnotePara);
    }
    
    // Run the macro
    analyzeDocument();
})();

    

So verwenden Sie dieses Makro in ONLYOFFICE:

  1. Öffnen Sie Ihr Dokument in ONLYOFFICE.
  2. Navigieren Sie zur Registerkarte „Ansicht“ und wählen Sie „Makros“.
  3. Erstellen Sie ein neues Makro und fügen Sie den Code ein.
  4. Führen Sie das Makro aus.
  5. Ein detaillierter Analysebericht wird am Ende Ihres Dokuments hinzugefügt.

Lassen Sie uns nun unser Makro ausführen und sehen, wie es funktioniert!

Dieses Makro ist ein wertvolles Tool für Fachleute, die Textanalyse- und Dokumentationsprozesse in einer modernen Büroumgebung automatisieren möchten. Wir hoffen, es ist eine nützliche Ergänzung für Ihre Arbeit.

Wir empfehlen Ihnen, die ONLYOFFICE API-Dokumentation zu erkunden, um eigene Makros zu erstellen oder diese zu erweitern. Wenn Sie Verbesserungsvorschläge oder Vorschläge für neue Makros haben, kontaktieren Sie uns gerne. Ihr Feedback hilft uns, weiterhin Tools zu entwickeln, die die Dokumenterstellung und -bearbeitung effizienter machen.

Über den Autor

How to analyze PDF form documents with ONLYOFFICE macro

Nützliche Links

ONLYOFFICE API-Methoden

ONLYOFFICE auf GitHub

Weitere ONLYOFFICE-Makros

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