added app.py

app.py

@@ -0,0 +1,78 @@
+import streamlit as st
+import pandas as pd
+import csv
+import chardet
+from io import StringIO, BytesIO
+import base64
+
+# Streamlit app title
+st.title('ASCII characters checker')
+st.text('This app will first check the csv file format.')
+st.text('It will then check the CSV file for any ASCII characters and convert them into searchable strings.')
+st.text('If found, download the file and search for <0x in your text editor.')
+
+# File uploader allows user to add their own CSV
+uploaded_file = st.file_uploader("Choose a CSV file", type=['csv'])
+
+# Checkbox for user to choose encoding conversion
+convert_to_utf8 = st.checkbox("Convert file to UTF-8", value=True)
+
+if uploaded_file is not None:
+    # To read file as string:
+    bytes_data = uploaded_file.getvalue()
+    
+    # Detect the encoding of the uploaded file
+    result = chardet.detect(bytes_data[:1024])  # Reading a sample for efficiency
+    original_encoding = result['encoding']
+    st.write(f"Detected encoding: {original_encoding}")  # Display the detected encoding
+    
+    # If the user wants to convert to UTF-8 and the file is not already UTF-8, convert it
+    if convert_to_utf8 and original_encoding != 'utf-8':
+        string_data = bytes_data.decode(original_encoding)  # Decode using the detected encoding
+        bytes_data = string_data.encode('utf-8')  # Encode to UTF-8
+    elif not convert_to_utf8:
+        # If user does not want to convert to UTF-8, ensure it's in ASCII
+        string_data = bytes_data.decode(original_encoding, errors='replace')  # Decode with replacement
+        bytes_data = string_data.encode('ascii', errors='replace')  # Encode to ASCII with replacement for non-ASCII characters
+    
+    # Convert bytes data to a StringIO object for pandas
+    string_io_data = StringIO(bytes_data.decode('utf-8' if convert_to_utf8 else 'ascii'))
+    
+    # Define a mapping of non-printable ASCII characters to their visible equivalents
+    ascii_replacements = {
+        i: f'<0x{i:02X}>' for i in range(128) if not chr(i).isprintable()
+    }
+    
+    # Function to replace non-printable ASCII characters
+    def replace_ascii_chars(s):
+        if isinstance(s, str):
+            return ''.join(ascii_replacements.get(ord(char), char) for char in s)
+        elif pd.isnull(s):
+            return s  # Return as is if the value is NaN
+        else:
+            return str(s)  # Convert non-string, non-null values to string
+    
+    # Read the CSV file into a pandas DataFrame
+    df = pd.read_csv(string_io_data, sep=',')
+    
+    # Apply the function to every cell in the DataFrame
+    cleaned_df = df.applymap(replace_ascii_chars)
+    
+    # Check if ASCII characters were found and replaced
+    ascii_found = any('<0x' in str(cell) for row in cleaned_df.values for cell in row)
+    if ascii_found:
+        # Display a message indicating that ASCII characters were found and replaced
+        st.info('ASCII characters were found and have been replaced with searchable strings.')
+    else:
+        # Optionally, display a message if no ASCII characters were found
+        st.write('No ASCII characters were found in the file.')
+    
+    # Convert DataFrame to CSV for download
+    output_csv = cleaned_df.to_csv(index=False, quoting=csv.QUOTE_NONNUMERIC, encoding='utf-8' if convert_to_utf8 else 'ascii')
+    
+    # Create a link for downloading the cleaned CSV
+    b64 = base64.b64encode(output_csv.encode()).decode()  # some strings <-> bytes conversions necessary here
+    href = f'<a href="data:file/csv;base64,{b64}" download="cleaned_file.csv">Download cleaned CSV file</a>'
+    st.markdown(href, unsafe_allow_html=True)
+    
+    st.write('File cleaned and ready for download.')