app.py

from flask import Flask, request, jsonify, send_file
from flask_cors import CORS
import pandas as pd
import os
import threading
import time
import re

app = Flask(__name__)
CORS(app)

UPLOAD_FOLDER = "/tmp"
SESSION_KEY_PREFIX = "data_tool_session_id"
app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
app.config['MAX_CONTENT_LENGTH'] = 512 * 1024 * 1024  # 512 MB

# Cleanup function runs every 10 mins and deletes files older than 60 mins
def clean_old_files(folder=UPLOAD_FOLDER, max_age=60):
    while True:
        now = time.time()
        for f in os.listdir(folder):
            path = os.path.join(folder, f)
            if os.path.isfile(path):
                if now - os.path.getmtime(path) > max_age * 60:
                    try:
                        os.remove(path)
                        print(f"[Cleanup] Deleted: {path}")
                    except Exception as e:
                        print(f"[Cleanup Error] {e}")
        time.sleep(600)  # Run every 10 minutes

# Start cleanup thread at launch
threading.Thread(target=clean_old_files, daemon=True).start()

def apply_instruction(df, instruction):
    instruction = instruction.lower()

    try:
        # Drop column
        match = re.search(r"drop column (\w+)", instruction)
        if match:
            df = df.drop(columns=[match.group(1)])

        # Remove duplicates
        if "remove duplicates" in instruction:
            df = df.drop_duplicates()

        # Drop missing values
        if "drop missing" in instruction or "remove null" in instruction:
            df = df.dropna()

        # Fill missing values
        match = re.search(r"fill missing.*with ([\w\.]+)", instruction)
        if match:
            val = match.group(1)
            try:
                val = float(val)
            except:
                pass
            df = df.fillna(val)

        # Sort
        match = re.search(r"sort by (\w+)( descending| desc)?", instruction)
        if match:
            col = match.group(1)
            ascending = not bool(match.group(2))
            df = df.sort_values(by=col, ascending=ascending)

        # Rename
        match = re.search(r"rename column (\w+) to (\w+)", instruction)
        if match:
            old, new = match.group(1), match.group(2)
            df = df.rename(columns={old: new})

        # Filter where col > val
        match = re.search(r"filter where (\w+) > (\d+)", instruction)
        if match:
            col, val = match.group(1), float(match.group(2))
            df = df[df[col] > val]

        # Group by and sum
        match = re.search(r"group by (\w+) and sum (\w+)", instruction)
        if match:
            group_col, sum_col = match.group(1), match.group(2)
            df = df.groupby(group_col)[sum_col].sum().reset_index()

        # Add column as sum
        match = re.search(r"add column (\w+) as (\w+) \+ (\w+)", instruction)
        if match:
            new_col, col1, col2 = match.group(1), match.group(2), match.group(3)
            df[new_col] = df[col1] + df[col2]

        # Normalize column
        match = re.search(r"normalize column (\w+)", instruction)
        if match:
            col = match.group(1)
            df[col] = (df[col] - df[col].min()) / (df[col].max() - df[col].min())

        # Standardize column
        match = re.search(r"standardize column (\w+)", instruction)
        if match:
            col = match.group(1)
            df[col] = (df[col] - df[col].mean()) / df[col].std()

        # Split column by comma
        match = re.search(r"split column (\w+) by comma", instruction)
        if match:
            col = match.group(1)
            df[[f"{col}_1", f"{col}_2"]] = df[col].str.split(",", expand=True)

        # Remove special characters
        match = re.search(r"remove special characters from (\w+)", instruction)
        if match:
            col = match.group(1)
            df[col] = df[col].astype(str).str.replace(r"[^a-zA-Z0-9]", "", regex=True)

    except Exception as e:
        return df, f"Error: {e}"

    return df, "success"

@app.route("/process", methods=["POST"])
def process_file():
    if "file" not in request.files or "instruction" not in request.form or "session_id" not in request.form:
        return jsonify({"error": "Missing file, instruction, or session_id"}), 400

    file = request.files["file"]
    instruction = request.form["instruction"]
    session_id = request.form["session_id"]

    try:
        df = pd.read_csv(file) if file.filename.endswith(".csv") else pd.read_excel(file)
    except Exception as e:
        return jsonify({"error": f"Failed to read file: {str(e)}"}), 400

    df, status = apply_instruction(df, instruction)

    filename = f"cleaned_{session_id}_{file.filename}"
    output_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
    df.to_csv(output_path, index=False)

    preview = df.head(10).to_dict(orient="records")
    return jsonify({
        "preview": preview,
        "download_url": f"/download/{filename}",
        "status": status
    })

@app.route("/download/<filename>", methods=["GET"])
def download_file(filename):
    session_id = request.args.get("session_id")
    if not session_id or f"_{session_id}_" not in filename:
        return jsonify({"error": "Unauthorized download attempt"}), 403

    path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
    if os.path.exists(path):
        return send_file(path, as_attachment=True)
    return jsonify({"error": "File not found"}), 404

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=7860)