Create resume_analysis.py

resume_analysis.py

@@ -0,0 +1,44 @@
+# resume_analysis.py
+
+import streamlit as st
+import fitz  # PyMuPDF
+
+def resume_analysis_page():
+    st.header("Resume Analysis and Optimization")
+
+    uploaded_file = st.file_uploader("Upload your resume (PDF format):", type="pdf")
+
+    if uploaded_file:
+        resume_text = extract_text_from_pdf(uploaded_file)
+        if resume_text:
+            st.success("Resume uploaded successfully!")
+            # Perform analysis
+            st.subheader("Extracted Information")
+            # Extracted data display
+            # For example, display extracted skills
+            skills = extract_skills(resume_text)
+            st.write("**Skills:**", ', '.join(skills))
+            # Provide optimization suggestions
+            st.subheader("Optimization Suggestions")
+            # Display suggestions
+            st.write("- Consider adding more industry-specific keywords.")
+            st.write("- Reformat your work experience for clarity.")
+        else:
+            st.error("Failed to extract text from resume.")
+
+def extract_text_from_pdf(pdf_file):
+    text = ""
+    try:
+        with fitz.open(stream=pdf_file.read(), filetype="pdf") as doc:
+            for page in doc:
+                text += page.get_text()
+        return text
+    except Exception as e:
+        st.error(f"Error extracting text: {e}")
+        return ""
+
+def extract_skills(text):
+    # Implement skill extraction logic
+    skills_list = ["Python", "Machine Learning", "Data Analysis", "SQL", "Communication", "Leadership"]
+    extracted_skills = [skill for skill in skills_list if skill.lower() in text.lower()]
+    return extracted_skills