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| import streamlit as st | |
| import itertools | |
| import os | |
| import funcs | |
| def about_course(): | |
| st.image("images//wireframe_header.jpg", use_column_width=True) | |
| st.title("Fundamentals of Resource Estimation") | |
| # get text from text_blocks: | |
| text = funcs.get_text_block("about_course.txt") | |
| st.write(text) | |
| st.write("") | |
| st.image("images//wireframe_header.jpg", use_column_width=True) | |
| st.markdown("# Presenters") | |
| # presenter = st.selectbox("", options=['Sean Horan', 'Valerie Wilson', 'Pierre Landry', 'Ian Weir']) | |
| for presenter in ['Sean Horan', 'Valerie Wilson', 'Pierre Landry', 'Ian Weir']: | |
| split_name = presenter.split(" ") | |
| lcase_name = (split_name[0] + "_" + split_name[1]).lower() | |
| ucase_name = (split_name[0] + "_" + split_name[1]) | |
| col1, col2 = st.beta_columns([1,2.5]) | |
| with col1: | |
| st.image("headshots//" + ucase_name + ".jpg", use_column_width=True) | |
| text = funcs.get_text_block("title_" + lcase_name + ".txt") | |
| st.markdown(text) | |
| with col2: | |
| text = funcs.get_text_block("resume_" + lcase_name + ".txt") | |
| st.write(text) | |