Create app.py

app.py

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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()