requirements.txt

pdfminer3
pyresparser
streamlit
pandas
pafy
plotly
pymysql
streamlit-tags
Pillow
youtube-dl
nltk
pdfminer3
spacy==2.3.5

app.py

@@ -0,0 +1,437 @@
+import streamlit as st
+import nltk
+import spacy
+import pandas as pd
+import base64, random
+import time, datetime
+from pyresparser import ResumeParser
+from pdfminer3.layout import LAParams, LTTextBox
+from pdfminer3.pdfpage import PDFPage
+from pdfminer3.pdfinterp import PDFResourceManager
+from pdfminer3.pdfinterp import PDFPageInterpreter
+from pdfminer3.converter import TextConverter
+import io, random
+from streamlit_tags import st_tags
+from PIL import Image
+import pymysql
+from Courses import ds_course, web_course, android_course, ios_course, uiux_course, resume_videos, interview_videos
+import pafy
+import plotly.express as px
+import youtube_dl
+
+nltk.download('punkt')
+nltk.download('stopwords')
+spacy.load("en_core_web_trf")
+
+
+def fetch_yt_video(link):
+    video = pafy.new(link)
+    return video.title
+
+
+def get_table_download_link(df, filename, text):
+    """Generates a link allowing the data in a given panda dataframe to be downloaded
+    in:  dataframe
+    out: href string
+    """
+    csv = df.to_csv(index=False)
+    b64 = base64.b64encode(csv.encode()).decode()  # some strings <-> bytes conversions necessary here
+    # href = f'<a href="data:file/csv;base64,{b64}">Download Report</a>'
+    href = f'<a href="data:file/csv;base64,{b64}" download="{filename}">{text}</a>'
+    return href
+
+
+def pdf_reader(file):
+    resource_manager = PDFResourceManager()
+    fake_file_handle = io.StringIO()
+    converter = TextConverter(resource_manager, fake_file_handle, laparams=LAParams())
+    page_interpreter = PDFPageInterpreter(resource_manager, converter)
+    with open(file, 'rb') as fh:
+        for page in PDFPage.get_pages(fh,
+                                      caching=True,
+                                      check_extractable=True):
+            page_interpreter.process_page(page)
+            print(page)
+        text = fake_file_handle.getvalue()
+
+    # close open handles
+    converter.close()
+    fake_file_handle.close()
+    return text
+
+
+def show_pdf(file_path):
+    with open(file_path, "rb") as f:
+        base64_pdf = base64.b64encode(f.read()).decode('utf-8')
+    # pdf_display = f'<embed src="data:application/pdf;base64,{base64_pdf}" width="700" height="1000" type="application/pdf">'
+    pdf_display = F'<iframe src="data:application/pdf;base64,{base64_pdf}" width="700" height="1000" type="application/pdf"></iframe>'
+    st.markdown(pdf_display, unsafe_allow_html=True)
+
+
+def course_recommender(course_list):
+    st.subheader("**Courses & Certificates🎓 Recommendations**")
+    c = 0
+    rec_course = []
+    no_of_reco = st.slider('Choose Number of Course Recommendations:', 1, 10, 4)
+    random.shuffle(course_list)
+    for c_name, c_link in course_list:
+        c += 1
+        st.markdown(f"({c}) [{c_name}]({c_link})")
+        rec_course.append(c_name)
+        if c == no_of_reco:
+            break
+    return rec_course
+
+
+# connection = pymysql.connect(host='localhost', user='root', password='')
+# # cursor = connection.# cursor()
+
+
+def insert_data(name, email, res_score, timestamp, no_of_pages, reco_field, cand_level, skills, recommended_skills,
+                courses):
+    DB_table_name = 'user_data'
+    insert_sql = "insert into " + DB_table_name + """
+    values (0,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)"""
+    rec_values = (
+        name, email, str(res_score), timestamp, str(no_of_pages), reco_field, cand_level, skills, recommended_skills,
+        courses)
+    # cursor.execute(insert_sql, rec_values)
+    connection.commit()
+
+
+st.set_page_config(
+    page_title="Smart CV Analyzer",
+    # page_icon='./Logo/SRA_Logo.ico',
+)
+
+
+def run():
+    st.title("Smart Resume Analyser")
+    st.sidebar.markdown("# Choose User")
+    activities = ["Normal User", "Admin"]
+    choice = st.sidebar.selectbox("Choose among the given options:", activities)
+    # link = '[©Developed by Spidy20](http://github.com/spidy20)'
+    # st.sidebar.markdown(link, unsafe_allow_html=True)
+    img = Image.open('./Logo/SRA_Logo.jpg')
+    img = img.resize((250, 250))
+    st.image(img)
+
+    # Create the DB
+    db_sql = """CREATE DATABASE IF NOT EXISTS SRA;"""
+    # # cursor.execute(db_sql)
+    # connection.select_db("sra")
+
+    # Create table
+    DB_table_name = 'user_data'
+    table_sql = "CREATE TABLE IF NOT EXISTS " + DB_table_name + """
+                    (ID INT NOT NULL AUTO_INCREMENT,
+                     Name varchar(100) NOT NULL,
+                     Email_ID VARCHAR(50) NOT NULL,
+                     resume_score VARCHAR(8) NOT NULL,
+                     Timestamp VARCHAR(50) NOT NULL,
+                     Page_no VARCHAR(5) NOT NULL,
+                     Predicted_Field VARCHAR(25) NOT NULL,
+                     User_level VARCHAR(30) NOT NULL,
+                     Actual_skills VARCHAR(300) NOT NULL,
+                     Recommended_skills VARCHAR(300) NOT NULL,
+                     Recommended_courses VARCHAR(600) NOT NULL,
+                     PRIMARY KEY (ID));
+                    """
+    # cursor.execute(table_sql)
+    if choice == 'Normal User':
+        # st.markdown('''<h4 style='text-align: left; color: #d73b5c;'>* Upload your resume, and get smart recommendation based on it."</h4>''',
+        #             unsafe_allow_html=True)
+        pdf_file = st.file_uploader("Choose your Resume", type=["pdf"])
+        if pdf_file is not None:
+            # with st.spinner('Uploading your Resume....'):
+            #     time.sleep(4)
+            save_image_path = './Uploaded_Resumes/' + pdf_file.name
+            with open(save_image_path, "wb") as f:
+                f.write(pdf_file.getbuffer())
+            show_pdf(save_image_path)
+            resume_data = ResumeParser(save_image_path).get_extracted_data()
+            if resume_data:
+                ## Get the whole resume data
+                resume_text = pdf_reader(save_image_path)
+
+                st.header("**Resume Analysis**")
+                st.success("Hello " + resume_data['name'])
+                st.subheader("**Your Basic info**")
+                try:
+                    st.text('Name: ' + resume_data['name'])
+                    st.text('Email: ' + resume_data['email'])
+                    st.text('Contact: ' + resume_data['mobile_number'])
+                    st.text('Resume pages: ' + str(resume_data['no_of_pages']))
+                except:
+                    pass
+                cand_level = ''
+                if resume_data['no_of_pages'] == 1:
+                    cand_level = "Fresher"
+                    st.markdown('''<h4 style='text-align: left; color: #d73b5c;'>You are looking Fresher.</h4>''',
+                                unsafe_allow_html=True)
+                elif resume_data['no_of_pages'] == 2:
+                    cand_level = "Intermediate"
+                    st.markdown('''<h4 style='text-align: left; color: #1ed760;'>You are at intermediate level!</h4>''',
+                                unsafe_allow_html=True)
+                elif resume_data['no_of_pages'] >= 3:
+                    cand_level = "Experienced"
+                    st.markdown('''<h4 style='text-align: left; color: #fba171;'>You are at experience level!''',
+                                unsafe_allow_html=True)
+
+                st.subheader("**Skills Recommendation💡**")
+                ## Skill shows
+                keywords = st_tags(label='### Skills that you have',
+                                   text='See our skills recommendation',
+                                   value=resume_data['skills'], key='1')
+
+                ##  recommendation
+                ds_keyword = ['tensorflow', 'keras', 'pytorch', 'machine learning', 'deep Learning', 'flask',
+                              'streamlit']
+                web_keyword = ['react', 'django', 'node jS', 'react js', 'php', 'laravel', 'magento', 'wordpress',
+                               'javascript', 'angular js', 'c#', 'flask']
+                android_keyword = ['android', 'android development', 'flutter', 'kotlin', 'xml', 'kivy']
+                ios_keyword = ['ios', 'ios development', 'swift', 'cocoa', 'cocoa touch', 'xcode']
+                uiux_keyword = ['ux', 'adobe xd', 'figma', 'zeplin', 'balsamiq', 'ui', 'prototyping', 'wireframes',
+                                'storyframes', 'adobe photoshop', 'photoshop', 'editing', 'adobe illustrator',
+                                'illustrator', 'adobe after effects', 'after effects', 'adobe premier pro',
+                                'premier pro', 'adobe indesign', 'indesign', 'wireframe', 'solid', 'grasp',
+                                'user research', 'user experience']
+
+                recommended_skills = []
+                reco_field = ''
+                rec_course = ''
+                ## Courses recommendation
+                for i in resume_data['skills']:
+                    ## Data science recommendation
+                    if i.lower() in ds_keyword:
+                        print(i.lower())
+                        reco_field = 'Data Science'
+                        st.success("** Our analysis says you are looking for Data Science Jobs.**")
+                        recommended_skills = ['Data Visualization', 'Predictive Analysis', 'Statistical Modeling',
+                                              'Data Mining', 'Clustering & Classification', 'Data Analytics',
+                                              'Quantitative Analysis', 'Web Scraping', 'ML Algorithms', 'Keras',
+                                              'Pytorch', 'Probability', 'Scikit-learn', 'Tensorflow', "Flask",
+                                              'Streamlit']
+                        recommended_keywords = st_tags(label='### Recommended skills for you.',
+                                                       text='Recommended skills generated from System',
+                                                       value=recommended_skills, key='2')
+                        st.markdown(
+                            '''<h4 style='text-align: left; color: #1ed760;'>Adding this skills to resume will boost🚀 the chances of getting a Job💼</h4>''',
+                            unsafe_allow_html=True)
+                        rec_course = course_recommender(ds_course)
+                        break
+
+                    ## Web development recommendation
+                    elif i.lower() in web_keyword:
+                        print(i.lower())
+                        reco_field = 'Web Development'
+                        st.success("** Our analysis says you are looking for Web Development Jobs **")
+                        recommended_skills = ['React', 'Django', 'Node JS', 'React JS', 'php', 'laravel', 'Magento',
+                                              'wordpress', 'Javascript', 'Angular JS', 'c#', 'Flask', 'SDK']
+                        recommended_keywords = st_tags(label='### Recommended skills for you.',
+                                                       text='Recommended skills generated from System',
+                                                       value=recommended_skills, key='3')
+                        st.markdown(
+                            '''<h4 style='text-align: left; color: #1ed760;'>Adding this skills to resume will boost🚀 the chances of getting a Job💼</h4>''',
+                            unsafe_allow_html=True)
+                        rec_course = course_recommender(web_course)
+                        break
+
+                    ## Android App Development
+                    elif i.lower() in android_keyword:
+                        print(i.lower())
+                        reco_field = 'Android Development'
+                        st.success("** Our analysis says you are looking for Android App Development Jobs **")
+                        recommended_skills = ['Android', 'Android development', 'Flutter', 'Kotlin', 'XML', 'Java',
+                                              'Kivy', 'GIT', 'SDK', 'SQLite']
+                        recommended_keywords = st_tags(label='### Recommended skills for you.',
+                                                       text='Recommended skills generated from System',
+                                                       value=recommended_skills, key='4')
+                        st.markdown(
+                            '''<h4 style='text-align: left; color: #1ed760;'>Adding this skills to resume will boost🚀 the chances of getting a Job💼</h4>''',
+                            unsafe_allow_html=True)
+                        rec_course = course_recommender(android_course)
+                        break
+
+                    ## IOS App Development
+                    elif i.lower() in ios_keyword:
+                        print(i.lower())
+                        reco_field = 'IOS Development'
+                        st.success("** Our analysis says you are looking for IOS App Development Jobs **")
+                        recommended_skills = ['IOS', 'IOS Development', 'Swift', 'Cocoa', 'Cocoa Touch', 'Xcode',
+                                              'Objective-C', 'SQLite', 'Plist', 'StoreKit', "UI-Kit", 'AV Foundation',
+                                              'Auto-Layout']
+                        recommended_keywords = st_tags(label='### Recommended skills for you.',
+                                                       text='Recommended skills generated from System',
+                                                       value=recommended_skills, key='5')
+                        st.markdown(
+                            '''<h4 style='text-align: left; color: #1ed760;'>Adding this skills to resume will boost🚀 the chances of getting a Job💼</h4>''',
+                            unsafe_allow_html=True)
+                        rec_course = course_recommender(ios_course)
+                        break
+
+                    ## Ui-UX Recommendation
+                    elif i.lower() in uiux_keyword:
+                        print(i.lower())
+                        reco_field = 'UI-UX Development'
+                        st.success("** Our analysis says you are looking for UI-UX Development Jobs **")
+                        recommended_skills = ['UI', 'User Experience', 'Adobe XD', 'Figma', 'Zeplin', 'Balsamiq',
+                                              'Prototyping', 'Wireframes', 'Storyframes', 'Adobe Photoshop', 'Editing',
+                                              'Illustrator', 'After Effects', 'Premier Pro', 'Indesign', 'Wireframe',
+                                              'Solid', 'Grasp', 'User Research']
+                        recommended_keywords = st_tags(label='### Recommended skills for you.',
+                                                       text='Recommended skills generated from System',
+                                                       value=recommended_skills, key='6')
+                        st.markdown(
+                            '''<h4 style='text-align: left; color: #1ed760;'>Adding this skills to resume will boost🚀 the chances of getting a Job💼</h4>''',
+                            unsafe_allow_html=True)
+                        rec_course = course_recommender(uiux_course)
+                        break
+
+                #
+                ## Insert into table
+                ts = time.time()
+                cur_date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
+                cur_time = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')
+                timestamp = str(cur_date + '_' + cur_time)
+
+                ### Resume writing recommendation
+                st.subheader("**Resume Tips & Ideas💡**")
+                resume_score = 0
+                if 'Objective' in resume_text:
+                    resume_score = resume_score + 20
+                    st.markdown(
+                        '''<h4 style='text-align: left; color: #1ed760;'>[+] Awesome! You have added Objective</h4>''',
+                        unsafe_allow_html=True)
+                else:
+                    st.markdown(
+                        '''<h4 style='text-align: left; color: #fabc10;'>[-] According to our recommendation please add your career objective, it will give your career intension to the Recruiters.</h4>''',
+                        unsafe_allow_html=True)
+
+                if 'Declaration' in resume_text:
+                    resume_score = resume_score + 20
+                    st.markdown(
+                        '''<h4 style='text-align: left; color: #1ed760;'>[+] Awesome! You have added Delcaration✍/h4>''',
+                        unsafe_allow_html=True)
+                else:
+                    st.markdown(
+                        '''<h4 style='text-align: left; color: #fabc10;'>[-] According to our recommendation please add Declaration✍. It will give the assurance that everything written on your resume is true and fully acknowledged by you</h4>''',
+                        unsafe_allow_html=True)
+
+                if 'Hobbies' or 'Interests' in resume_text:
+                    resume_score = resume_score + 20
+                    st.markdown(
+                        '''<h4 style='text-align: left; color: #1ed760;'>[+] Awesome! You have added your Hobbies⚽</h4>''',
+                        unsafe_allow_html=True)
+                else:
+                    st.markdown(
+                        '''<h4 style='text-align: left; color: #fabc10;'>[-] According to our recommendation please add Hobbies⚽. It will show your persnality to the Recruiters and give the assurance that you are fit for this role or not.</h4>''',
+                        unsafe_allow_html=True)
+
+                if 'Achievements' in resume_text:
+                    resume_score = resume_score + 20
+                    st.markdown(
+                        '''<h4 style='text-align: left; color: #1ed760;'>[+] Awesome! You have added your Achievements🏅 </h4>''',
+                        unsafe_allow_html=True)
+                else:
+                    st.markdown(
+                        '''<h4 style='text-align: left; color: #fabc10;'>[-] According to our recommendation please add Achievements🏅. It will show that you are capable for the required position.</h4>''',
+                        unsafe_allow_html=True)
+
+                if 'Projects' in resume_text:
+                    resume_score = resume_score + 20
+                    st.markdown(
+                        '''<h4 style='text-align: left; color: #1ed760;'>[+] Awesome! You have added your Projects👨‍💻 </h4>''',
+                        unsafe_allow_html=True)
+                else:
+                    st.markdown(
+                        '''<h4 style='text-align: left; color: #fabc10;'>[-] According to our recommendation please add Projects👨‍💻. It will show that you have done work related the required position or not.</h4>''',
+                        unsafe_allow_html=True)
+
+                st.subheader("**Resume Score📝**")
+                st.markdown(
+                    """
+                    <style>
+                        .stProgress > div > div > div > div {
+                            background-color: #d73b5c;
+                        }
+                    </style>""",
+                    unsafe_allow_html=True,
+                )
+                my_bar = st.progress(0)
+                score = 0
+                for percent_complete in range(resume_score):
+                    score += 1
+                    time.sleep(0.1)
+                    my_bar.progress(percent_complete + 1)
+                st.success('** Your Resume Writing Score: ' + str(score) + '**')
+                st.warning(
+                    "** Note: This score is calculated based on the content that you have added in your Resume. **")
+                st.balloons()
+
+                insert_data(resume_data['name'], resume_data['email'], str(resume_score), timestamp,
+                            str(resume_data['no_of_pages']), reco_field, cand_level, str(resume_data['skills']),
+                            str(recommended_skills), str(rec_course))
+
+                ## Resume writing video
+                st.header("**Bonus Video for Resume Writing Tips💡**")
+                resume_vid = random.choice(resume_videos)
+                res_vid_title = fetch_yt_video(resume_vid)
+                st.subheader("✅ **" + res_vid_title + "**")
+                st.video(resume_vid)
+
+                ## Interview Preparation Video
+                st.header("**Bonus Video for Interview👨‍💼 Tips💡**")
+                interview_vid = random.choice(interview_videos)
+                int_vid_title = fetch_yt_video(interview_vid)
+                st.subheader("✅ **" + int_vid_title + "**")
+                st.video(interview_vid)
+
+                connection.commit()
+            else:
+                st.error('Something went wrong..')
+    else:
+        ## Admin Side
+        st.success('Welcome to Admin Side')
+        # st.sidebar.subheader('**ID / Password Required!**')
+
+        ad_user = st.text_input("Username")
+        ad_password = st.text_input("Password", type='password')
+        if st.button('Login'):
+            if ad_user == 'machine_learning_hub' and ad_password == 'mlhub123':
+                st.success("Welcome Kushal")
+                # Display Data
+                # cursor.execute('''SELECT*FROM user_data''')
+                ## data = # cursor.fetchall()
+                st.header("**User's👨‍💻 Data**")
+                df = pd.DataFrame(data, columns=['ID', 'Name', 'Email', 'Resume Score', 'Timestamp', 'Total Page',
+                                                 'Predicted Field', 'User Level', 'Actual Skills', 'Recommended Skills',
+                                                 'Recommended Course'])
+                st.dataframe(df)
+                st.markdown(get_table_download_link(df, 'User_Data.csv', 'Download Report'), unsafe_allow_html=True)
+                ## Admin Side Data
+                query = 'select * from user_data;'
+                plot_data = pd.read_sql(query, connection)
+
+                ## Pie chart for predicted field recommendations
+                labels = plot_data.Predicted_Field.unique()
+                print(labels)
+                values = plot_data.Predicted_Field.value_counts()
+                print(values)
+                st.subheader("📈 **Pie-Chart for Predicted Field Recommendations**")
+                fig = px.pie(df, values=values, names=labels, title='Predicted Field according to the Skills')
+                st.plotly_chart(fig)
+
+                ### Pie chart for User's👨‍💻 Experienced Level
+                labels = plot_data.User_level.unique()
+                values = plot_data.User_level.value_counts()
+                st.subheader("📈 ** Pie-Chart for User's👨‍💻 Experienced Level**")
+                fig = px.pie(df, values=values, names=labels, title="Pie-Chart📈 for User's👨‍💻 Experienced Level")
+                st.plotly_chart(fig)
+
+
+            else:
+                st.error("Wrong ID & Password Provided")
+
+
+run()