How can I export SQL Decimal() values to CSV using Streamlit?

Below is an explanation of what’s likely going wrong and some suggestions to fix it.

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Key Issues

1. File Pointer Position:
   When you open a file in write mode and write data to it, the file pointer ends up at the end of the file. If you pass that same file handle (or its contents) to Streamlit’s download button without resetting the pointer, the download button sees an empty stream.

2. Using a Disk File vs. In‑Memory Buffer:
   Even if the file is written correctly on disk, passing a file handle opened in write-mode directly to Streamlit isn’t ideal. The Streamlit docs suggest using a string, bytes, or a file‑like object that already holds the content ready for download (typically with the pointer at the start).

3. Decimal Conversion:
   When using SQL queries, your output contains Python’s Decimal objects. Converting that list of dictionaries (or rows) to a Pandas DataFrame using eval might fail if Decimal objects are included. One strategy is to convert each Decimal to a float or string before writing to CSV.

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Recommended Fixes

1. Use an In‑Memory Buffer

Instead of writing to a file on disk, use Python’s io.StringIO (for text) or io.BytesIO (if you need bytes) so that you have full control over the data and pointer. For example:

PYTHONCopied
import csv
import io
import streamlit as st

# Suppose out is the list of rows you want to write.
# For demonstration, let's assume out is a list of lists.
# If you have a list of dictionaries, you might first extract headers.

# Optionally convert Decimal objects to strings/floats:
def convert_row(row):
    return [str(item) if isinstance(item, Decimal) else item for item in row]

# Using StringIO as an in-memory file
buffer = io.StringIO()
writer = csv.writer(buffer, delimiter=",")

# Write rows (converting each row if needed)
for row in out:
    writer.writerow(convert_row(row))

# IMPORTANT: Move to the beginning of the StringIO buffer
buffer.seek(0)

# Now pass the in-memory data to st.download_button
st.download_button(
    label="Download data as CSV",
    data=buffer.getvalue(),   # data as a string
    file_name="filename.csv",
    mime="text/csv"
)

2. Reset the File Pointer if Using an On‑Disk File

If you really need to use a file on disk (for example, for debugging), be sure to set the file pointer back to the beginning before passing it to Streamlit:

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with open(filename, mode='w+', newline='') as file_to_output:
    writer = csv.writer(file_to_output, delimiter=",")
    writer.writerows(out)
    # Move the pointer back to the beginning
    file_to_output.seek(0)
    st.download_button(
        label="Download data as CSV",
        data=file_to_output.read(),  # Read the entire file contents
        file_name="filename.csv",
        mime="text/csv"
    )

However, using an in-memory buffer is often preferable in Streamlit apps.

3. Convert Decimal Objects

If your data rows come in as dictionaries or lists that include Decimal objects, you may need to ensure they are converted into a CSV‑compatible string or numeric type. One pattern is to use a converter function as shown in the convert_row function above. Alternatively, if you have dictionaries you might do:

PYTHONCopied
import csv
import io

def convert_decimal(obj):
    if isinstance(obj, Decimal):
        return str(obj)  # or float(obj) as needed
    return obj

buffer = io.StringIO()
csv_writer = csv.DictWriter(buffer, fieldnames=out[0].keys())
csv_writer.writeheader()
for row in out:
    csv_writer.writerow({k: convert_decimal(v) for k, v in row.items()})
buffer.seek(0)
st.download_button(
    label="Download data as CSV",
    data=buffer.getvalue(),
    file_name="filename.csv",
    mime="text/csv"
)

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Summary

• Use an in‑memory buffer (like io.StringIO) rather than a file handle directly to ensure you’re passing the complete data stream.
• Reset the pointer (using seek(0)) before passing the content to st.download_button.
• Convert Decimal objects (or any non‑serializable types) to string/float before writing them to CSV.

This should resolve the blank file issue and allow you to download the correct CSV data.