Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+from wordcloud import WordCloud, STOPWORDS
+import matplotlib.pyplot as plt
+import PyPDF2
+from docx import Document
+import plotly.express as px
+import base64
+from io import BytesIO
+
+# Functions for file reading
+def read_txt(file):
+    return file.getvalue().decode("utf-8")
+
+def read_docx(file):
+    doc = Document(file)
+    return " ".join([para.text for para in doc.paragraphs])
+
+def read_pdf(file):
+    pdf = PyPDF2.PdfReader(file)
+    return " ".join([page.extract_text() for page in pdf.pages])
+
+# Function to filter out stopwords
+def filter_stopwords(text, additional_stopwords=[]):
+    words = text.split()
+    all_stopwords = STOPWORDS.union(set(additional_stopwords))
+    filtered_words = [word for word in words if word.lower() not in all_stopwords]
+    return " ".join(filtered_words)
+
+# Function to create download link for plot
+def get_image_download_link(buffered, format_):
+    image_base64 = base64.b64encode(buffered.getvalue()).decode()
+    return f'<a href="data:image/{format_};base64,{image_base64}" download="wordcloud.{format_}">Download Plot as {format_}</a>'
+
+# Function to generate a download link for a DataFrame
+def get_table_download_link(df, filename, file_label):
+    csv = df.to_csv(index=False)
+    b64 = base64.b64encode(csv.encode()).decode()
+    return f'<a href="data:file/csv;base64,{b64}" download="{filename}">{file_label}</a>'
+
+# Streamlit code
+st.title("Word Cloud Generator")
+st.subheader("📁 Upload a pdf, docx or text file to generate a word cloud")
+
+uploaded_file = st.file_uploader("Choose a file", type=["txt", "pdf", "docx"])
+st.set_option('deprecation.showPyplotGlobalUse', False)
+
+if uploaded_file:
+    file_details = {"FileName": uploaded_file.name, "FileType": uploaded_file.type, "FileSize": uploaded_file.size}
+    st.write(file_details)
+
+    # Check the file type and read the file
+    if uploaded_file.type == "text/plain":
+        text = read_txt(uploaded_file)
+    elif uploaded_file.type == "application/pdf":
+        text = read_pdf(uploaded_file)
+    elif uploaded_file.type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
+        text = read_docx(uploaded_file)
+    else:
+        st.error("File type not supported. Please upload a txt, pdf or docx file.")
+        st.stop()
+
+    # Generate word count table
+    words = text.split()
+    word_count = pd.DataFrame({'Word': words}).groupby('Word').size().reset_index(name='Count').sort_values('Count', ascending=False)
+
+    # Sidebar: Checkbox and Multiselect box for stopwords
+    use_standard_stopwords = st.sidebar.checkbox("Use standard stopwords?", True)
+    top_words = word_count['Word'].head(50).tolist()
+    additional_stopwords = st.sidebar.multiselect("Additional stopwords:", sorted(top_words))
+
+    if use_standard_stopwords:
+        all_stopwords = STOPWORDS.union(set(additional_stopwords))
+    else:
+        all_stopwords = set(additional_stopwords)
+
+    text = filter_stopwords(text, all_stopwords)
+
+    if text:
+        # Word Cloud dimensions
+        width = st.sidebar.slider("Select Word Cloud Width", 400, 2000, 1200, 50)
+        height = st.sidebar.slider("Select Word Cloud Height", 200, 2000, 800, 50)
+
+        # Generate wordcloud
+        st.subheader("Generated Word Cloud")
+        fig, ax = plt.subplots(figsize=(width/100, height/100))  # Convert pixels to inches for figsize
+        wordcloud_img = WordCloud(width=width, height=height, background_color='white', max_words=200, contour_width=3, contour_color='steelblue').generate(text)
+        ax.imshow(wordcloud_img, interpolation='bilinear')
+        ax.axis('off')
+
+        # Save plot functionality
+        format_ = st.selectbox("Select file format to save the plot", ["png", "jpeg", "svg", "pdf"])
+        resolution = st.slider("Select Resolution", 100, 500, 300, 50)
+        # Generate word count table
+        st.subheader("Word Count Table")
+        words = text.split()
+        word_count = pd.DataFrame({'Word': words}).groupby('Word').size().reset_index(name='Count').sort_values('Count', ascending=False)
+        st.write(word_count)
+    st.pyplot(fig)
+    if st.button(f"Save as {format_}"):
+        buffered = BytesIO()
+        plt.savefig(buffered, format=format_, dpi=resolution)
+        st.markdown(get_image_download_link(buffered, format_), unsafe_allow_html=True)
+
+
+    # Word count table at the end
+    st.sidebar.markdown("---")
+    st.sidebar.subheader("Learn Advanced AI| Hope to Skill with Irfan Malik")
+    # add a youtube video
+    st.sidebar.video("https://www.youtube.com/watch?v=vCKF1vYVNTs&list=PLxf3-FrL8GzRALeq_9BtdQclN6SF4bTCG")
+    st.sidebar.markdown("---")
+    # add author name and info
+    st.sidebar.markdown("Created by: [Virtual Student](https://github.com/dashboard)")
+    st.sidebar.markdown("website:(https://xevenskills.com)")
+
+
+
+
+    st.subheader("Word Count Table")
+    st.write(word_count)
+    # Provide download link for table
+    if st.button('Download Word Count Table as CSV'):
+        st.markdown(get_table_download_link(word_count, "word_count.csv", "Click Here to Download"), unsafe_allow_html=True)
+