Flask app scenarios to handle large CSV uploads, triggering MemoryError on processing
I'm upgrading from an older version and I'm working with a `MemoryError` when trying to upload and process large CSV files using my Flask application. The application uses the `pandas` library to read the CSV data into a DataFrame. For smaller files, everything works perfectly, but when I attempt to upload files larger than about 50 MB, it crashes with the following behavior: ``` MemoryError: Unable to allocate 123.4 MiB for an array with shape (123456, 10) and data type float64 ``` I'm using Flask 2.1.1 and pandas 1.4.2. Here's a simplified version of my upload route: ```python from flask import Flask, request, jsonify import pandas as pd app = Flask(__name__) @app.route('/upload', methods=['POST']) def upload_file(): if 'file' not in request.files: return jsonify({'behavior': 'No file uploaded'}), 400 file = request.files['file'] try: # Attempt to read the CSV file with pandas df = pd.read_csv(file) # Further processing... return jsonify({'message': 'File processed successfully'}), 200 except Exception as e: return jsonify({'behavior': str(e)}), 500 ``` I’ve already tried increasing the available memory on the server, but it still fails for larger files. I also considered using `chunksize` in `pd.read_csv()` to process the file in smaller chunks, but I'm not sure how to aggregate results from those chunks effectively. Could anyone provide guidance on how to handle larger CSV uploads without running into memory issues? I would appreciate any code examples or strategies to manage this situation effectively. I'm on Windows 10 using the latest version of Python. Any pointers in the right direction?