74c862faec
User-Friendly Interface: The Streamlit interface is intuitive, allowing users to easily input text and get readability scores. Comprehensive Analysis: The tool covers a wide range of readability metrics, providing detailed insights into the text's readability. Actionable Tips: Each readability score is accompanied by actionable tips, helping users improve their content based on the analysis. Additional Insights: The inclusion of additional metrics like reading time, syllable count, and word count provides a thorough analysis of the text. Suggested Improvements: Error Handling: Add error handling for cases where the text input might be empty or too short for certain readability metrics. Code Modularization: Refactor the code to encapsulate readability calculations and markdown generation into separate functions. This will make the code more modular and easier to maintain. Performance Optimization: Optimize the readability calculation by avoiding redundant calculations if the text hasn't changed. Code Readability: Add docstrings and comments to explain the purpose of functions and complex code blocks. Ensure consistent formatting and adherence to PEP8 standards.
158 lines
7.1 KiB
Python
158 lines
7.1 KiB
Python
import textstat
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import streamlit as st
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st.set_page_config(layout="wide", page_title="Text Readability Analyzer", page_icon=":book:")
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st.title("📖 Text Readability Analyzer: Making Your Content Easy to Read")
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st.write("""
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This tool is your guide to writing content that's easy for your audience to understand.
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Just paste in a sample of your text, and we'll break down the readability scores and offer actionable tips!
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""")
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def analyze_text(test_data):
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"""
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Analyzes the readability of the provided text and returns a dictionary with the results.
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Parameters:
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test_data (str): The text to be analyzed.
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Returns:
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dict: A dictionary containing readability scores and additional metrics.
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"""
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return {
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"Flesch Reading Ease": {
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"score": textstat.flesch_reading_ease(test_data),
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"description": "This score rates your text on a scale of 0-100, with higher scores being easier to read.",
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"tips": [
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"Score below 30? Simplify your text by breaking down complex sentences, using shorter words, and avoiding jargon.",
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"Score around 60-70? You're in the 'standard' range.",
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"Score over 90? Your text is very easy to read. Add some complexity or sophistication if needed."
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]
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},
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"Flesch-Kincaid Grade Level": {
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"score": textstat.flesch_kincaid_grade(test_data),
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"description": "This formula estimates the US school grade level needed to understand your text.",
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"tips": [
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"High Score? Your writing might be too complex for your target audience.",
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"Low Score? Your audience might find the text too simple.",
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"Match Your Audience: Tailor the complexity to your readers."
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]
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},
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"SMOG Index": {
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"score": textstat.smog_index(test_data),
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"description": "This formula measures text complexity by looking at the number of long words and sentences.",
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"tips": [
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"Best for texts with at least 30 sentences.",
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"Adjust complexity to match your target audience."
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]
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},
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"Coleman-Liau Index": {
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"score": textstat.coleman_liau_index(test_data),
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"description": "This formula uses sentence length and the number of syllables per word to estimate the reading level."
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},
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"Automated Readability Index (ARI)": {
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"score": textstat.automated_readability_index(test_data),
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"description": "Estimates the grade level required to comprehend your text."
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},
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"Dale-Chall Readability Score": {
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"score": textstat.dale_chall_readability_score(test_data),
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"description": "Focuses on the number of uncommon words (not on a list of 3000 common words) and sentence length.",
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"tips": [
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"Easy to Understand: Aim for a score around the reading level of your audience.",
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"High School Level? Scores between 9 and 12 indicate a high school reading level.",
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"Beyond High School? Scores above 12 are usually for a college-level audience."
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]
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},
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"Gunning Fog": {
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"score": textstat.gunning_fog(test_data),
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"description": "Calculates the grade level required to understand the text."
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},
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"Linsear Write Formula": {
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"score": textstat.linsear_write_formula(test_data),
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"description": "Estimates the US grade level needed to understand the text."
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},
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"Text Standard (Consensus)": {
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"score": textstat.text_standard(test_data),
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"description": "A consensus estimate of the US grade level needed to understand your text, based on multiple readability scores."
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},
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"Spache Readability": {
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"score": textstat.spache_readability(test_data),
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"description": "Best for analyzing text for children, typically up to grade 4.",
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"tips": [
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"Considers the number of unfamiliar words and the length of sentences."
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]
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},
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"McAlpine EFLAW": {
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"score": textstat.mcalpine_eflaw(test_data),
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"description": "Evaluates text for foreign language learners, focusing on 'miniwords' and sentence length.",
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"tips": [
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"Target Score: Aim for a score of 25 or less."
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]
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},
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"Reading Time": {
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"score": textstat.reading_time(test_data),
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"description": "Estimated reading time in minutes."
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},
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"Syllable Count": {
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"score": textstat.syllable_count(test_data),
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"description": "The number of syllables in the text."
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},
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"Word Count": {
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"score": textstat.lexicon_count(test_data),
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"description": "The number of words in the text."
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},
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"Sentence Count": {
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"score": textstat.sentence_count(test_data),
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"description": "The number of sentences in the text."
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},
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"Character Count": {
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"score": textstat.char_count(test_data),
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"description": "The number of characters in the text."
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},
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"Letter Count (without punctuation)": {
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"score": textstat.letter_count(test_data),
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"description": "The number of letters without punctuation."
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},
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"Polysyllable Count": {
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"score": textstat.polysyllabcount(test_data),
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"description": "The number of polysyllabic words in the text."
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},
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"Monosyllable Count": {
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"score": textstat.monosyllabcount(test_data),
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"description": "The number of monosyllabic words in the text."
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}
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}
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text_input = st.text_area("Paste your text here:", height=200)
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if st.button("Analyze!"):
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with st.spinner("Analyzing your text..."):
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test_data = text_input
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if not test_data.strip():
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st.error("Please enter text to analyze.")
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else:
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results = analyze_text(test_data)
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st.subheader("Readability Scores:")
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st.write("---")
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for metric, data in results.items():
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st.markdown(f"**{metric}:** {data['score']}")
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st.markdown(f"* **What It Means:** {data['description']}")
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if 'tips' in data:
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st.markdown("* **Actionable Tips:**")
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for tip in data['tips']:
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st.markdown(f" * {tip}")
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st.write(" ")
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st.subheader("Key Takeaways:")
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st.write("---")
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st.markdown("""
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* **Don't Be Afraid to Simplify!** Often, simpler language makes content more impactful and easier to digest.
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* **Aim for a Reading Level Appropriate for Your Audience:** Consider the education level, background, and familiarity of your readers.
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* **Use Short Sentences:** This makes your content more scannable and easier to read.
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* **Write for Everyone:** Accessibility should always be a priority. When in doubt, aim for clear, concise language!
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""")
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