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ConstructionComplexityCalculator.py

@@ -1,112 +1,108 @@
-from flask import Flask, request, render_template, send_from_directory
-import stanza
-import pandas as pd
-import os
-import platform
-import scipy.stats as stats
-
-# Set a directory within the /tmp directory for Stanza resources
-stanza_dir = os.path.join('/tmp', 'stanza_resources')
-os.makedirs(stanza_dir, exist_ok=True)
-
-# Initialize the Stanza pipeline with the custom directory
-nlp = stanza.Pipeline("en", dir=stanza_dir)
-
-app = Flask(__name__)
-
-# Function to calculate diversity (Shannon's entropy) of a sentence
-def sentence_diversity_calc(tags):
-    pairs = [(tags[i], tags[i+1]) for i in range(len(tags) - 1)]
-    pair_counts = {pair: pairs.count(pair) for pair in pairs}
-    total_pairs = sum(pair_counts.values())
-    probabilities = [count / total_pairs for count in pair_counts.values()]
-    return stats.entropy(probabilities, base=2)
-
-# Function to calculate the productivity of each sentence
-def sentence_productivity_calc(words, tags):
-    word_tag_pairs = list(zip(words, tags))
-    pair_counts = {pair: word_tag_pairs.count(pair) for pair in word_tag_pairs}
-    total_pairs = sum(pair_counts.values())
-    probabilities = [count / total_pairs for count in pair_counts.values()]
-    H_WT = stats.entropy(probabilities, base=2)
-    
-    tag_counts = {tag: tags.count(tag) for tag in tags}
-    total_tags = sum(tag_counts.values())
-    tag_probabilities = [count / total_tags for count in tag_counts.values()]
-    H_T = stats.entropy(tag_probabilities, base=2)
-    
-    H_WT_given_T = H_WT - H_T
-    return H_WT_given_T + 1
-
-# Function to calculate the document complexity
-def document_complexity_calc(sentences, doc):
-    N = len(sentences)
-    total_complexity = total_diversity = total_productivity = 0
-
-    for sentence in sentences:
-        sen_words = [word.text.lower() for word in sentence.words if word.upos != "PUNCT"]
-        sen_pos = [word.xpos for word in sentence.words if word.upos != "PUNCT"]
-        
-        diversity = sentence_diversity_calc(sen_pos)
-        productivity = sentence_productivity_calc(sen_words, sen_pos)
-        
-        total_complexity += diversity * productivity
-        total_diversity += diversity
-        total_productivity += productivity
-
-    return total_complexity / N, total_diversity / N, total_productivity / N
-
-@app.route('/')
-def index():
-    return render_template('index.html')
-
-@app.route('/process', methods=['POST'])
-def process():
-    text = request.form.get('text', '')
-    files = request.files.getlist('files')
-    results = []
-
-    if text:
-        doc = nlp(text)
-        complexity, avg_diversity, avg_productivity = document_complexity_calc(doc.sentences, doc)
-        return f"""
-        Complexity score: {complexity}<br>
-        Diversity: {avg_diversity}<br>
-        Productivity: {avg_productivity}
-        """
-
-    elif files:
-        for uploaded_file in files:
-            if not uploaded_file.filename.endswith('.txt'):
-                return "Only .txt files are allowed."
-
-            content = uploaded_file.read().decode('utf-8')
-            doc = nlp(content)
-            complexity, avg_diversity, avg_productivity = document_complexity_calc(doc.sentences, doc)
-            results.append({'filename': uploaded_file.filename,
-                            'complexity': complexity,
-                            'diversity': avg_diversity,
-                            'productivity': avg_productivity})
-
-        df = pd.DataFrame(results)
-
-        # Save the CSV file to a known directory
-        downloads_folder = "/app/Downloads"
-        os.makedirs(downloads_folder, exist_ok=True)
-        csv_filename = os.path.join(downloads_folder, 'complexity_scores.csv')
-        df.to_csv(csv_filename, index=False)
-
-        # Provide a link to download the file
-        return f"""
-        Finished processing. <a href="/download/complexity_scores.csv">Download the CSV file</a>.
-        """
-
-    return "No input provided"
-
-@app.route('/download/<filename>')
-def download_file(filename):
-    downloads_folder = "/app/Downloads"
-    return send_from_directory(directory=downloads_folder, path=filename, as_attachment=True)
-
-if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=5000, debug=False)
+from flask import Flask, request, render_template, send_from_directory
+import stanza
+import pandas as pd
+import os
+import platform
+import scipy.stats as stats
+
+app = Flask(__name__)
+
+# Initialize the Stanza pipeline
+nlp = stanza.Pipeline("en", dir="/app/stanza_resources")  # Adjust path if needed
+
+# Function to calculate diversity (Shannon's entropy) of a sentence
+def sentence_diversity_calc(tags):
+    pairs = [(tags[i], tags[i+1]) for i in range(len(tags) - 1)]
+    pair_counts = {pair: pairs.count(pair) for pair in pairs}
+    total_pairs = sum(pair_counts.values())
+    probabilities = [count / total_pairs for count in pair_counts.values()]
+    return stats.entropy(probabilities, base=2)
+
+# Function to calculate the productivity of each sentence
+def sentence_productivity_calc(words, tags):
+    word_tag_pairs = list(zip(words, tags))
+    pair_counts = {pair: word_tag_pairs.count(pair) for pair in word_tag_pairs}
+    total_pairs = sum(pair_counts.values())
+    probabilities = [count / total_pairs for count in pair_counts.values()]
+    H_WT = stats.entropy(probabilities, base=2)
+    
+    tag_counts = {tag: tags.count(tag) for tag in tags}
+    total_tags = sum(tag_counts.values())
+    tag_probabilities = [count / total_tags for count in tag_counts.values()]
+    H_T = stats.entropy(tag_probabilities, base=2)
+    
+    H_WT_given_T = H_WT - H_T
+    return H_WT_given_T + 1
+
+# Function to calculate the document complexity
+def document_complexity_calc(sentences, doc):
+    N = len(sentences)
+    total_complexity = total_diversity = total_productivity = 0
+
+    for sentence in sentences:
+        sen_words = [word.text.lower() for word in sentence.words if word.upos != "PUNCT"]
+        sen_pos = [word.xpos for word in sentence.words if word.upos != "PUNCT"]
+        
+        diversity = sentence_diversity_calc(sen_pos)
+        productivity = sentence_productivity_calc(sen_words, sen_pos)
+        
+        total_complexity += diversity * productivity
+        total_diversity += diversity
+        total_productivity += productivity
+
+    return total_complexity / N, total_diversity / N, total_productivity / N
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/process', methods=['POST'])
+def process():
+    text = request.form.get('text', '')
+    files = request.files.getlist('files')
+    results = []
+
+    if text:
+        doc = nlp(text)
+        complexity, avg_diversity, avg_productivity = document_complexity_calc(doc.sentences, doc)
+        return f"""
+        Complexity score: {complexity}<br>
+        Diversity: {avg_diversity}<br>
+        Productivity: {avg_productivity}
+        """
+
+    elif files:
+        for uploaded_file in files:
+            if not uploaded_file.filename.endswith('.txt'):
+                return "Only .txt files are allowed."
+
+            content = uploaded_file.read().decode('utf-8')
+            doc = nlp(content)
+            complexity, avg_diversity, avg_productivity = document_complexity_calc(doc.sentences, doc)
+            results.append({'filename': uploaded_file.filename,
+                            'complexity': complexity,
+                            'diversity': avg_diversity,
+                            'productivity': avg_productivity})
+
+        df = pd.DataFrame(results)
+
+        # Save the CSV file to a known directory
+        downloads_folder = "/app/Downloads"
+        os.makedirs(downloads_folder, exist_ok=True)
+        csv_filename = os.path.join(downloads_folder, 'complexity_scores.csv')
+        df.to_csv(csv_filename, index=False)
+
+        # Provide a link to download the file
+        return f"""
+        Finished processing. <a href="/download/complexity_scores.csv">Download the CSV file</a>.
+        """
+
+    return "No input provided"
+
+@app.route('/download/<filename>')
+def download_file(filename):
+    downloads_folder = "/app/Downloads"
+    return send_from_directory(directory=downloads_folder, path=filename, as_attachment=True)
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=5000, debug=False)

Dockerfile

@@ -1,21 +1,18 @@
-# Use the official Python image from the Docker Hub
-FROM python:3.12-slim
-
-# Set the working directory in the container
-WORKDIR /app
-
-# Copy the requirements file into the container
-COPY requirements.txt .
-
-# Install the dependencies
-RUN pip install --upgrade pip && \
-    pip install --no-cache-dir -r requirements.txt
-
-# Copy the rest of the application code into the container
-COPY . .
-
-# Expose the port the app runs on
-EXPOSE 5000
-
-# Define the command to run the application using gunicorn
-CMD ["gunicorn", "-w", "4", "-b", "0.0.0.0:5000", "ConstructionComplexityCalculator:app"]
+FROM python:3.12-slim
+
+WORKDIR /app
+
+# Copy default.zip
+COPY default.zip /app/stanza_resources
+
+# Install dependencies
+COPY requirements.txt .
+RUN pip install --upgrade pip && \
+    pip install --no-cache-dir -r requirements.txt
+
+# Copy your application code
+COPY . .
+
+EXPOSE 5000
+
+CMD ["gunicorn", "-w", "4", "-b", "0.0.0.0:5000", "ConstructionComplexityCalculator:app"]