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| import pandas as pd | |
| import streamlit as st | |
| from difflib import SequenceMatcher | |
| def read_csv_or_excel(file): | |
| # Read CSV or Excel file | |
| if file.name.endswith('.csv'): | |
| return pd.read_csv(file) | |
| elif file.name.endswith('.xlsx') or file.name.endswith('.xls'): | |
| return pd.read_excel(file) | |
| else: | |
| raise ValueError("Unsupported file format. Only CSV and Excel files are supported.") | |
| def find_exact_matches(df1, df2, column_name): | |
| # Find rows with exact matches in the specified column | |
| matches = pd.merge(df1, df2, on=column_name, how='inner') | |
| return matches | |
| def find_similar_texts(df1, df2, column_name, threshold=0.8): | |
| # Find rows with similar texts in the specified column | |
| similar_texts = [] | |
| for index1, row1 in df1.iterrows(): | |
| for index2, row2 in df2.iterrows(): | |
| similarity = SequenceMatcher(None, str(row1[column_name]), str(row2[column_name])).ratio() | |
| if similarity >= threshold: | |
| similar_texts.append((index1, index2, row1[column_name], row2[column_name])) | |
| return similar_texts | |
| def main(): | |
| st.title("Item Comparison App") | |
| # Upload files | |
| st.header("Upload Files") | |
| warehouse_file = st.file_uploader("Upload Warehouse Item Stocks (CSV or Excel)") | |
| industry_file = st.file_uploader("Upload Industry Item Stocks (CSV or Excel)") | |
| if warehouse_file is not None and industry_file is not None: | |
| # Read files | |
| warehouse_df = read_csv_or_excel(warehouse_file) | |
| industry_df = read_csv_or_excel(industry_file) | |
| # Get column names | |
| warehouse_columns = warehouse_df.columns.tolist() | |
| industry_columns = industry_df.columns.tolist() | |
| # Select columns using dropdowns | |
| st.header("Select Columns") | |
| warehouse_column = st.selectbox("Choose column from warehouse item stocks:", warehouse_columns) | |
| industry_column = st.selectbox("Choose column from industry item stocks:", industry_columns) | |
| # Find exact matches | |
| exact_matches = find_exact_matches(warehouse_df, industry_df, warehouse_column) | |
| # Find similar texts | |
| similar_texts = find_similar_texts(warehouse_df, industry_df, warehouse_column) | |
| # Display results | |
| st.header("Exact Matches") | |
| st.write(exact_matches) | |
| st.header("Similar Texts") | |
| for text_pair in similar_texts: | |
| st.write(f"Row {text_pair[0]} in warehouse item stocks is similar to Row {text_pair[1]} in industry item stocks:") | |
| st.write(f"Warehouse: {text_pair[2]}") | |
| st.write(f"Industry: {text_pair[3]}") | |
| st.write("") | |
| if __name__ == "__main__": | |
| main() | |